International Conference on�Gender and Technology - �2025

CSLT action plan for the 12+2 Stations for the �Cognitive Sciences labyrinth

Sections

Updates from Faculty members/mentors

Updates

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Please finalize the ready station by Thursday 2nd of January.

please suggest VR video ideas which are simple representing the bias

Overall exhibition coordinators

Updates

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Digitalization

Updates

Two options:

1. Canva: website

https://cognitivelabyrinthgenderxtechnology.my.canva.site/dagax03pv-8

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• Jotform

https://form.jotform.com/243644784038464

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Cognitive Sciences Labyrinth

Updates

Work in progress

Base Station - Entry

Updates

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Theme based Stations

Theme and Team member details

Theme and Resources required �for the stations/activity

#1 - Gender, Society, and Representation �in Emerging Technologies

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#1 - Gender, Society, and Representation �in Emerging Technologies

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#1 - Gender, Society, and Representation �in Emerging Technologies

Detailed overview of planned activity

• Guess the Pioneer! /Guess Who?
• The station won't be running at all times; timings will be announced shortly. Functional - twice a day.
• The activity will be completely offline, participants will be shown flashcards with pictures of pioneers (both male and female) and their task is to guess their contributions.
• After the activity, they will be made to compare the number of female pioneers they were able to guess as well as the male pioneers. Biases will be debriefed, and Quizlet online flashcards will be shared so that participants can learn more about the inventors and contributors to technological development.
• Hall of Fame: Two walls - posters/pictures of key figures in tech (male and women) and mentions their contributions. (will be done in the wall calendar style - i.e. January - Name and Photo of the pioneer, February - the contribution. Therefore, the participant will be able to flip through the pages, making it interactive in nature.
• Representation of Women in STEM: Third wall - for posters showing statistics on underrepresentation of women in STEM fields from UNESCO reports, Statistica etc.

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Resources required

• Flashcards, answer sheets, ballpoint pens, whiteboard and marker, posters

#1 - Gender, Society, and Representation �in Emerging Technologies

Information on posters

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https://www.stemwomen.com/women-in-stem-statistics-progress-and-challenges

#1 - Gender, Society, and Representation �in Emerging Technologies

Information on posters

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• The UNESCO report highlights that women make up only 35% of STEM graduates globally, a figure that has remained stagnant over the past decade

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#2 - Environment, natural resources, �and gender

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Addressing the intersection of gender and technology in tackling environmental and natural resource management and distribution
• Suggested topics include how gendered perspectives can enhance environmental tech solutions, the role of women in natural resource innovation, and the impact of such technologies on gender equity in communities

#2 - Environment, natural resources, �and gender

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Station #2 layout

Wall 3

Wall 1 - Poster 1

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• Introduce biases and their impact on policies and solutions (context - less inclusive data impacting efficiency of solutions)

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• Connect it to next poster

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Wall 2 - Poster 2

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• Introduce characters
• Comic conversation illustrating biases

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Wall 2 - Poster 3

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• 3 Statistics

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Wall 3 - Poster 4

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• Overcoming biases
• End Quote

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Table / Stand

• QR Code cards or bookmarks in cardholder with an attractive banner (Feed your Mind— Scan here!)

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Wall #2 Post. 2 Post. 3

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Wall #1

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Wall #3

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QR Code

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(Takeaway)

Wall 1 - Poster 1 (42 seconds)

Wall 2 - Poster 2 layout - 3 mins

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Wall 3 - Poster 3 (30 seconds)

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Highlights from research -

Despite extensive research on gender vulnerability to climate change, gender-focused measures remain scarce in projects, urban planning, and policies. UN data shows just 1.5% of climate financing supports women (Oxfam,2023).

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Less than 2% of national climate strategies consider the unique needs of girls, despite their heightened vulnerability to climate change, environmental degradation, biodiversity loss and gender inequality (WAGGGS, 2022).

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A survey found only 10% of respondents collect gender-disaggregated data regularly, while about half neither collect nor plan to collect such data for environmental policies (OECD, 2021).

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Wall 4 - Poster 4 - (40 seconds)

Environmental change has specific differentiated impacts on women and girls or on men and boys. Using a gender-specific approach to examine these complex linkages is therefore an appropriate way to investigate the dynamic relationships between environmental change and gender equality, as well as between impacts on sustainability and the realization of women’s rights and empowerment.

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Global Gender and Environment Outlook, UN Environment Programme, 2018

End Quote

Transforming Our Biases

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Take a look at how we can overcome these biases -

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• Collect diverse, representative, and disaggregated data to ensure all groups are fairly represented.�
• Design policies that address the overlapping needs of marginalized identities through inclusive consultation.�
• Ensure equitable access to solutions and actively include all populations in policy design and implementation.

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Table or Stand - QR Code Cards Holder

#3 - Gender, livelihood, and the �future of work

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Investigating the influence of technologies like AI, robotics, and blockchain on gender dynamics in the workplace
• Focus areas can include gender disparities in tech jobs, the potential for inclusive work environments in the gig and care economies, �and how automation might affect gender roles in various industries

#3 - Gender, livelihood, and the �future of work

Detailed overview of planned activity

• Explain each bias in detail after taking participants through the history of the development of AI technologies

Activity:

• Participants will be asked to choose from a deck of cards arranged on the table. The cards will have scenarios that we see in workplaces. Participants can choose scenarios and decide which bias is coming in play in each scenarios. The correct bias will be written on the card behind the scenario (similar to flashcards).
• This game can adopt a mixed-method approach, where biases are first explained in detail, followed by a quiz that presents various scenarios, requiring participants to identify the appropriate bias frame accurately.

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Resources required

• Posters detailing the 3 biases with real-life examples
• Flashcards with scenarios
• Poster showing the timeline of the development of AI technologies like Alexa, Siri
• QR code posters leading to digital activity

#3 - Gender, livelihood, and the �future of work

"The Future of Work: Powered by Equality, Driven by Talent!"

🎢 The world of work is transforming—fast! But here’s the twist: the future doesn’t work unless everyone works. 🌟

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💡 Picture this:

Women leading industries 🚀

Livelihoods built on fairness 🌈

Creativity unleashed, unboxed, and unstoppable

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Break the bias. Build the dream. Let’s make the future of work a stage where everyone shines, because talent knows no gender. 💼✨

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Ready to work for a better tomorrow? Let’s make it happen!

Wall #2

Center piece with QR code

Wall #1

Wall #3

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Wall #1 - Feedback Loop Bias:

Poster elements

Feedback Loop Bias: Understanding How Systems Reinforce Their Own Patterns

"Breaking the Bias Loop for Women"

Feedback loop bias often targets women, keeping them stuck in cycles of disadvantage. In tech, workplaces, and society, it:

💡 Reinforces gender stereotypes, limiting career growth.�💡 Creates unfair barriers in hiring, promotions, and pay.�💡 Amplifies the gender gap, especially in emerging fields like AI and robotics.

By disrupting this loop, we can empower women to thrive, innovate, and lead in every industry. The future is equal!

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QR code content

• Show the content of poster in dynamic manner in digital platform with a video or website �

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Wall #3

Center piece with QR code

Wall #2

Wall #1

Wall #1 - Content layout{What is Feedback Loop Bias?}

Feedback Loop Bias: Understanding How Systems Reinforce Their Own Patterns

What is Feedback Loop Bias?

Feedback loop bias occurs when the outcomes of a system are fed back into it, reinforcing existing patterns or behaviors. This cycle amplifies biases and can distort decision-making. It creates a circular pattern where the system's output influences its future input, resulting in a self-reinforcing cycle.

Key Concept:

Input: New data or behavior enters the system.

Output: System produces an outcome based on the input.

Feedback: The output is fed back into the system, influencing future outcomes.

This feedback cycle can lead to the reinforcement of biases within systems like algorithms, social media, and decision-making processes.

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Real-World Example: Social Media Algorithms

Social media platforms use algorithms to show you content based on your past interactions. These algorithms are designed to keep you engaged by presenting content that you are likely to interact with. Here's how feedback loop bias plays out:

Initial Engagement: When you engage with posts (like, comment, share) that align with your personal views or preferences, the algorithm takes note of this behavior.

Reinforcement: The algorithm then serves you more content similar to what you’ve interacted with before, whether it's news articles, posts, or videos that align with your existing beliefs or interests.

Echo Chamber Effect: Over time, this creates an echo chamber where you are only exposed to ideas and information that reinforce your worldview, while other perspectives become less visible.

Amplified Bias: As a result, your beliefs may become more extreme, and you may lose awareness of other viewpoints. The system continues to amplify this cycle, making it harder to break out of the feedback loop.

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Consequences of Feedback Loop Bias

Polarization: It reinforces extreme views, reducing exposure to diverse perspectives.

Misinformation: Sensational content can spread more easily when feedback loops favor it, leading to misinformation.

Skewed Decision-Making: Biases shape decisions by limiting the variety of information available for consideration.

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How to Break the Bias

Seek Diverse Perspectives: Explore content that challenges your views to break free from your content bubble and reduce confirmation bias.

Question Algorithms: Be aware of how algorithms filter content, and seek out diverse sources to counteract the biases they reinforce.

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Wall #2 -Ingroup Bias

Wall #2

Center piece

Wall #1

Wall #3

Poster elements

• "Ingroup Bias: Why We Favor 'Us' Over 'Them'"

Ingroup bias makes us favor our own gender, often without realizing it.

How it shows up:

• Favoritism: We trust our gender more.
• Bias: We judge the other gender unfairly.
• Solidarity: Our group feels stronger, but others are left out.

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QR code content

• Show the content of poster in dynamicmanner in digat platform with a video or website �

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Wall #2 - Content layout {Ingroup Bias}

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How to Address Gender-Based Ingroup Bias

Encourage Inclusive Teams:

Form diverse teams that require collaboration across gender lines, fostering mutual respect and understanding.

Focus on Merit:

Establish objective criteria for evaluations and decisions, ensuring contributions are assessed based on skills and performance, not gender.

Create Shared Goals:

Emphasize collective team success over individual or subgroup contributions, reducing the focus on gender differences.

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Real-World Example of the Ingroup Effect:

In a workplace, individuals may unconsciously favor colleagues of the same gender, creating an ingroup bias.

Scenario: During a team project, male employees may perceive other men as more competent or better suited for leadership roles, even when female colleagues have equal or superior qualifications. Similarly, women might feel more comfortable collaborating with other women and may undervalue the contributions of male colleagues.

Outcome: This bias reinforces stereotypes, creates division, and limits opportunities for collaboration or merit-based recognition.

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"Ingroup Bias: Why We Favor 'Us' Over 'Them'“

The ingroup effect is a cognitive bias where individuals show preference or favoritism toward members of their own group (ingroup) while being less favorable or even hostile to those outside the group (outgroup). This bias often stems from a desire for social identity and belonging.

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Key Features of the Ingroup Effect

Favoritism: Viewing ingroup members as more trustworthy, likable, or competent.

Bias: Judging outgroup members more harshly or stereotyping them unfairly.

Group Solidarity: Increased cohesion within the ingroup, often leading to exclusion or rivalry with the outgroup.

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"Approximately 90% of men and women hold fundamental biases against women.“

The Gender Social Norms Index (GSNI) quantifies biases against women, capturing people’s attitudes on women’s roles along four key dimensions: political, educational, economic and physical integrity.

United Nations Development Programme. (2023). 2023 Gender Social Norms Index (GSNI). from https://hdr.undp.org/content/2023-gender-social-norms-index-gsni#/indicies/GSNI

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Wall #3 - Framing Effect:

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Center piece

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Poster elements

• Framing Effect: How Presentation Shapes Perception

How you say it shapes what people do.

• Positive Frame: Focus on the benefits, and they’ll say “yes.”
• Negative Frame: Highlight the risks, and they’ll back away.

Same facts, different choices—perception is everything!

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QR code content

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Wall #3 - Content layout {Framing Effect}

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Framing Effect: How Presentation Shapes Perception

The framing effect is a cognitive bias where people’s decisions are influenced by how information is presented rather than the information itself. The same facts or outcomes can lead to different choices depending on whether they are framed positively or negatively.

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Key Features of the Framing Effect

Positive Frame: Emphasizing benefits or favorable outcomes makes people more likely to choose an option.

Negative Frame: Highlighting risks or unfavorable outcomes often leads to avoidance or rejection of the same option.

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Real-World Example: Health Communication

Positive Frame: A medical treatment has a 90% survival rate.

Negative Frame: The same treatment has a 10% mortality rate.

Although both statements convey the same information, people are more likely to favor the treatment when the survival rate is emphasized (positive framing) rather than the mortality rate (negative framing).

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Impact of the Framing Effect

Shapes public opinion, marketing decisions, and policymaking.

Can lead to biased or irrational choices if individuals don’t analyze the underlying facts.

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How to Overcome the Framing Effect

Focus on Facts: Look beyond the wording and evaluate the actual data.

Consider Alternative Frames: Reframe the information to see if it changes your perspective.

Seek Objective Analysis: Use logical reasoning or consult unbiased sources to make informed decisions.

Understanding the framing effect helps in making more rational choices and resisting manipulation.

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A woman applies for a leadership role, and her qualifications are framed as "nurturing and supportive," while a man's are framed as "decisive and authoritative." Despite having similar qualifications, the woman may be perceived as less suited for the role, highlighting the impact of framing effect bias.

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Take Away Infographic Cards talking about the bias

Center table items

QR code scanner for the game

Flashcards of scenarios

Front: A small graphic

Back: Brief explanations of situation

Participant to match the scenarios with the bias.

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Example of situations in flashcard

Scenario 1: Gender and Promotion Opportunities

• Scenario: "At a tech company, two employees, Alex and Maria, both contribute equally to a major project. However, Alex, who is a male employee, is frequently praised by the team leader for his leadership and contributions during meetings. Meanwhile, Maria, who is equally involved, gets little recognition despite her crucial role. Over time, the manager begins to consider Alex for a promotion based on his consistent visibility, while Maria’s efforts go unnoticed."
• Question: Which bias is at play here?
• A) Feedback Loop Bias
• B) Ingroup Bias
• C) Framing Effect

Correct Answer: A) Feedback Loop Bias

Explanation: Feedback Loop Bias is evident here because Alex is receiving positive feedback that reinforces his visibility and chances of promotion. Maria's contributions, though equally valuable, are overlooked, reinforcing the cycle of feedback that favors Alex.

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The Awakening of Universal Motherhood

An Address given by Amma on the occasion of the Global Peace Initiative of Women Religious and Spiritual Leaders, at Palais des Nations, Geneva, on October 7th, 2002.

Amma stated that women can perform any task as well as, or even better than, men. She emphasized that women are not intellectually inferior and possess the willpower and creativity to excel in all areas, including the spiritual path.

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Amma explained that a man’s mind often becomes attached to his thoughts and actions, much like stagnant water that doesn't flow. He finds it hard to shift focus, leading to a blending of his professional and family life. In contrast, women have an innate ability to separate these spheres, balancing roles as mothers, wives, and friends with ease. Feminine energy is fluid, allowing women to succeed in both family and professional life while providing guidance and confidence to their families.

Amma's call for reforming outdated social and religious systems aligns with the future of work, where equality, inclusion, and progress are key. As the workplace evolves, it is essential to dismantle systemic barriers that limit women's potential. Just as Amma advocates for condemning injustice and violence against women, organizations and leaders must ensure that workplaces foster equal opportunities and promote fairness. Embracing these values will enable women to thrive in the workforce, contributing to a more balanced and just future of work.

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#4 - Women’s health and sanitation �in the digital age

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Examination of the role of digital health technologies, telemedicine, and Al in improving women's health and sanitation
• Discussions may include the impact of wearable tech on women's health monitoring, digital platforms for mental health support, �and innovations in community health tech

#4 - Women’s health and sanitation �in the digital age

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• Activity 1 - Diagnosis Dilemma
• Participants will be made to do a quiz where the most common diseases among men and women would be presented randomly. The participant has to choose which gender is more likely to have the disease.
• After choosing the option, the participants will get instant feedback on each of the answer, tackling their stereotype regarding each disease and their association of a disease with a particular gender instantly.
• At the completion of the quiz, the participant would be able to see their overall score and given an explanation on why it happens by introducing the biases to them.

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#4 - Women’s health and sanitation �in the digital age

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• Activity 1 - Overcoming the stereotype bias
• Participants will be made to do a quiz where the most common diseases among men and women would be presented randomly. The participant has to choose which gender is more likely to have the disease.
• After choosing the option, the participants will get instant feedback on each of the answer, tackling their stereotype regarding each disease and their association of a disease with a particular gender instantly.
• At the completion of the quiz, the participant would be able to see their overall score and given an explanation on why it happens by introducing the biases to them.

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#4 - Women’s health and sanitation �in the digital age

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• Activity 2 - "Reflecting on Open Defecation"

Step 1: Context Setting (30 seconds)

• Begin by explaining that 1.5 billion people globally still lack access to safely managed sanitation, and many resort to open defecation.
• Highlight the importance of understanding this issue from a psychological and social perspective.

Step 2: Ask participants to close their eyes and imagine:

• They are in an open field with no toilet nearby.
• People are passing by at a distance, and there’s little privacy.
• They hear footsteps or voices nearby.
• Use sound effects (e.g., rustling leaves, distant chatter) to create an immersive atmosphere.

Prompt Reflection

As they imagine the scenario, ask them to think about:

• How they feel emotionally (e.g., vulnerable, embarrassed, exposed).
• Whether they would feel safe or comfortable.
• How this would affect their dignity and self-esteem.

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#4 - Women’s health and sanitation �in the digital age

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Step 3: Sharing Experiences (1-2 minute)

• Individual Reflection
• Provide paper slips for participants to note their emotions and reactions.
• What immediate concerns came to your mind (e.g., safety, hygiene, shame)?
• How did you feel about the lack of privacy and dignity?

For men: Concerns about hygiene and dignity.

For women: Amplified concerns about safety (e.g., risk of harassment or assault), societal judgment, and health issues, especially during menstruation or pregnancy.

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Step 4;Reflection and Discussion on Solutions (30 seconds - 1 minute)

Will ask visitor to reflect on the solution and how to overcome it.

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#4 - Women’s health and sanitation �in the digital age

Key facts( From WHO)

• In 2022, 57% of the global population (4.6 billion people) used a safely managed sanitation service.
• Over 1.5 billion people still do not have basic sanitation services, such as private toilets.
• Of these, 419 million still defecate in the open, for example in street gutters, behind bushes or into open bodies of water.

The world is on track to eliminate open defecation by 2030, if not by 2025, but historical rates of progress would need to double for the world to achieve universal coverage with basic sanitation services by 2030.

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#4 - Women’s health and sanitation �in the digital age

Amma has been instrumental in empowering rural women to build toilets, transforming sanitation challenges into economic opportunities. She states, "Our approach is to take what has been a persistent social ill – open defecation and lack of basic hygiene – and transform it into an economic opportunity for people below the poverty line while simultaneously improving public health outcomes for the community at large."

On the Right to Sanitation: "Every child, rich or poor, has the right to survive, the right to health, the right to a future.

-sanjay Wijesekera, UNICEF's Chief of Water, Sanitation, and Hygiene

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#4 - Women’s health and sanitation �in the digital age

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• Activity 3 - Mansplaining solutions.

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IN THIS ACTIVITY ; TWO BOARD WILL BE SET UP:

• One board is available for brainstorming ideas (for men).
• The other board is covered and will remain hidden until later (for women”s feedback)

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1.Men’s brainstorming: Men are given a specific health or sanitations problem faced by women. For example- the problem could be ‘’How can be make it easier for women to track their menstrual cycles”?.

• They will brainstorm and write their ideas on the open board .They might come up with the ideas like “create an app with daily reminders”.

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2. women’s feedback: After a few hours of brainstorming ,the covered board is revealed to a group of women .The women will review the ideas and provide their thoughts and feedback.

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3. Co-designing solutions: Later on, men and women coming to the station can work on the pre-existing ideas/feedbacks, communicate with each other and come up with their own solutions to the question.

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#4 - Women’s health and sanitation �in the digital age

• Activity 4 -What’s Missing From Your Feed?

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This activity involves a social media feed mockup that shows two type of content.

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1. On the left, They will see typical sanitation topics like “recycling” or “eco-toilets”-topics that are more general and widely discussed .
2. on the right, gender-specific issues like “menstrual hygiene”are blurred out,showing that these topics are often ignored or are only being discussed by the female community. Participants will be made to guess what’s hidden, before proceeding on to the ne

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• How algorithms are perpetuating it.

On the left the placard will only be showing generic sanitation issues. However ,this can lead to missing out on

important topics like menstrual hygiene,as the algorithm is not promoting diverse or gender-specific content.

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• CALL FOR ACTION.

A QR code will be provided with a message : “SCAN TO EXPLORE TWO FEEDS AND UNCOVER WHAT IS MISSING”.

By scanning it,people can see side -by-side examples of what a balanced feed should look like- one that includes both general and gender-specific issues.

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#4 - Women’s health and sanitation �in the digital age

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Resources required

• Two whiteboards, whiteboard markers, sticky notes.
• Printed posters.
• QR codes leading to activities .
• whiteboards stand.

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#5 - Safety and security: gendered perspectives on new technologies

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

• Evaluating the implications of advancements in information and cyber security, Al, and data analytics for gendered safety
• Proposed topics include online harassment, the development of gender-sensitive security protocols, and the role of Al in �predicting and preventing gender-based violence

https://mentalhealthathome.org/2020/04/24/what-is-victim-blaming/

#5 - Safety and security: gendered perspectives on new technologies

Mission : Detection

• Playing Detective (Online Crime board): Having the participants act like an detective, searching for biases in a crime board for technology facilitated harassment. The participants can choose the missions. When the players identify the bias, the facilitators would give more information about the specific bias. These would be in form of clues. The crime board will include newspaper article headlines and interviews with authorities, perpetrators or general society members. It would also mention statistics.
• Address Gender Bias (Solution Box)-One box/bowl- participants can put their solutions to overcome the biases
• Feedback board -what the participants feel to write about the activity they have done, whatever they feel like to write, like solutions etc.
• Brochure: List of cognitive biases, instructional manual for game, biases for specific crime scenarios (revenge porn, sextortion, cyber stalking), statistics

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Resources required

• Board
• Solution Box/Bowl
• Sticky Notes
• Online Crime Board Link/QR

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Visual Representation

ChatGPT image generation

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Virtual Crime Board

https://prezi.com/lofpfomafblg/crime-board-template/

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Safety and Security in the Online World: Decoding the Gendered Blame Game

Proposed Title

Practical Examples

Revenge Porn/ Non Consensual Sharing of Sexual Images

Scenario: A woman shares intimate photos with her partner, who leaks them after a breakup.

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Victim-Blaming: Society often unfairly blames women for sharing intimate photos, perpetuating the stereotype that they should have known better or acted more responsibly. This shifts the focus away from the perpetrator's wrongdoing.

"She Should Have Known Better."

Gender Bias: There is a tendency to stereotype women as being more emotional or irrational, which can lead to dismissive attitudes towards their distress and the serious violation of their privacy.

"Women Are Reckless with Their Emotions."

Double Standards: Men who share intimate photos are often not judged as harshly as women. This double standard reinforces harmful stereotypes about gender and sexuality. This stereotype also excuses the perpetrator's behavior by suggesting that men are naturally inclined to act irresponsibly or maliciously, thereby normalizing harmful actions.

"Men Will Be Men.”

Reputation Damage: Women are more likely to face severe social and professional consequences due to leaked intimate photos, stemming from stereotypes that judge women's worth based on their sexual behavior, suggesting that their worth is tied to their perceived purity or modesty.

"Her Reputation Is Ruined."

Statistics: Revenge Porn �(Non-Consensual Distribution of Intimate Images)

UK Data (Revenge Porn Helpline, 2022 Report):

4,406 reports in 2021, a 40% increase from 2020.

75% of cases were reported by female victims.

Cases of sextortion increased fivefold from 2020 to 2021.

US Data (2023 Survey, Center for Innovative Public Health Research):

Approximately 10.4 million Americans (~4% of the population) have faced threats or actual postings of explicit images without consent.

Women are nearly five times more likely to be targeted than men.

Median victim age: 23 years.

India Data (National Crime Records Bureau, Section 67A of the IT Act):

Cases increased from 1,111 in 2018 to 1,814 in 2020.

A study by the Cyber and Law Foundation found that 27% of internet users aged 13-45 in India had been victims of revenge porn.

98% of cybercrime victims, predominantly women, do not report incidents due to societal stigma.

https://www.researchgate.net/publication/380296219

Other Research

1. Marijke Naezer & Lotte van Oosterhout (2021) Only sluts love sexting: youth, sexual norms and non-consensual sharing of digital sexual images, Journal of Gender Studies, 30:1, 79-90, DOI: 10.1080/09589236.2020.1799767

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• Amudhan S, Sharma MK, Anand N, Johnson J. “Snapping, sharing and receiving blame”: A systematic review on psychosocial factors of victim blaming in non‑consensual pornography. Ind Psychiatry J 2024;33:3-12 –The review highlights psychosocial and cultural factors influencing victim blaming in non-consensual pornography, emphasizing gender stereotypes, perceived immorality, and societal attitudes

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• Zvi L. The Double Standard Toward Female and Male Victims of Non-consensual Dissemination of Intimate Images. J Interpers Violence. 2022 Nov;37(21-22):NP20146-NP20167. doi: 10.1177/08862605211050109. Epub 2021 Oct 12. PMID: 34636679. – Female victims of self-taken intimate images face higher blame and negative perceptions, particularly from male participants

Other Practical Examples

Cyberstalking

Scenario: A user posts about their vacation and receives threatening messages from a stalker.

Victim-Blaming: There is a stereotype that people, especially women, should be more cautious about what they share online. This can lead to victim-blaming, where the user is criticized for posting about their vacation rather than focusing on the stalker's inappropriate behavior.

Gender Stereotypes: Women are often stereotyped as being more vulnerable to stalking and harassment. This can result in dismissive attitudes towards their concerns, with people assuming they are overreacting or being overly sensitive.

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Sextortion

Scenario: A hacker obtains private photos of a user and threatens to leak them unless paid.

Victim-Blaming: The user is criticized for having private photos rather than focusing on the hacker's criminal behavior: "Why did they even take such photos?"

Just-World Fallacy: This leads people to believe the world is fair, believing that bad things happen only to those who deserve them: "If they hadn’t taken those pictures, this wouldn’t happen.”

Reputation Damage: Women, in particular, might face severe social and professional consequences if the photos are leaked, stemming from stereotypes that judge a woman's worth based on their sexual behavior.

#6 - Gender, education, and cultural shifts through technology

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Exploring how technologies like VP, AR, and loT can foster gender equality in education and cultural settings
• Topics may include gender inclusivity in STEM education, digital literacy programs for women, cultural impacts of �tech-enabled learning environments, and initiatives for increasing female participation in tech careers

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#7 - Socio-cultural change, access to technology, and gender equity politics

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Analyzing how emerging technologies influence socio-cultural change, access to technology, and the politics of gender equity
• Discussions can cover policy frameworks for gender-sensitive tech governance, the role of social media in gender activism, �digital divide issues, and the impact of digital culture on gender norms
• Additionally, this topic will explore how technology can help identify our humanness: unifying features across races, genders, and cultures, and strengthen it towards positive outcomes, while respectfully acknowledging and including diversity

#7 - Socio-cultural change, access to technology, and gender equity politics

Detailed overview of planned activity

. Reverse discrimination Bias can be exhibited through different perceptual activities where the Reverse discrimination bias is intertwined with the perceptual bias. Demonstration of Evaluative and Aversive conditioning leading to bias.

. Linking Perceptual Bias with scriptural references:

Perceptual activity: Based on the preferences of target audience.

Pratyaksha - Visual and direct perception. Example: A transparent box with representation of gender

Anumana- Inferential perception. Example: An opaque box with toys inside. Example: An opaque box with representation of gender.

Agama- Descriptive and referential perception. Example: A description of two scenario.

Evaluation:

Pramana- Right perception. Viparyaya- False Perception.

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Resources required

• Two Boxes- 1 transparent box, 1 opaque box.
• Chart paper, Marker, Clay to make toys or Toys that are already available.
• A small device with buttons-Colour coded- Red One with shock like sensation, Green button with no sensation.

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#8 - Building inclusive resilience to �disaster and climate change

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

• Addressing the role of gender in developing tech solutions for disaster resilience and climate change adaptation
• Proposed topics include gender-sensitive disaster management systems, the use of big data for climate resilience through a gender lens, �and the participation of women in tech-driven environmental initiatives

#8 - Building inclusive resilience to �disaster and climate change

Resilience Quest: Gender Perspectives in Disaster Management (Card Game)

Objective

The game aims to:

• Engage participants in exploring disaster management scenarios through a gender lens.
• Identify and discuss biases that affect decision-making in disaster response and recovery.
• Foster collaborative problem-solving and critical thinking regarding gender inclusivity in disaster management.

Game Structure

Participants will draw cards representing various disaster scenarios, each associated with specific biases. They will discuss the scenario, identify the bias, and propose solutions.

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Resources required

Physical Requirements: The game requires minimal physical setup, making it easy to implement.

Engagement Level: The format encourages active participation, suitable for both light-hearted interactions and serious discussions

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4 card categories

Card Color Coding

Each card will be color-coded according to the stage of disaster management:

• Pre-Disaster: Earth (Prithvi: stability and preparation)
• Emergency: Fire (Agni: urgency and transformation)
• Rehabilitation: Water (Jala: healing)
• Reconstruction: Air (Vayu: movement and new beginnings)

Example of Scenarios

Scenario: Pre-Disaster�Planners rely on past evacuation strategies that excluded women’s input, reinforcing traditional methods.

• Identified Bias: Confirmation Bias
• Proposed Solution: Use evidence-based approaches to evaluate past strategies and incorporate women's insights for improvement.

Scenario: Emergency

Women are primarily viewed as caregivers during relief efforts, preventing them from taking on leadership roles.

• Identified Bias: Stereotyping
• Proposed Solution: Assign roles based on skills and train women in leadership positions for emergency response.

Scenario: Rehabilitation

Men dominate resource distribution meetings due to a shared belief among decision-makers that women’s input is secondary.

• Identified Bias: Groupthink
• Proposed Solution: Facilitate discussions that challenge the consensus and actively include women’s perspectives to diversify decision-making.

Scenario : Reconstruction�A committee attributes women’s reluctance to participate in planning sessions to lack of interest, ignoring systemic barriers like time constraints or childcare responsibilities.

• Identified Bias: Fundamental Attribution Error
• Proposed Solution: Assess situational barriers preventing women’s participation and address them with practical solutions, such as offering childcare support.

Venn Diagram: Poster

Title: In Times of Crisis, Leadership Knows No Gender

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1. Pre-Disaster Stage

• Exclusion from Decision-Making: Women are often excluded from emergency planning and preparedness decisions, leading to a lack of representation in risk assessment and resource allocation.
• Stereotyping: Women’s roles are often stereotyped as caregivers, limiting their involvement in formal preparedness activities.
• Limited Access to Information: Women may have less access to critical information regarding disaster preparedness due to societal norms.

2. Emergency Stage

• Increased Vulnerability: Women, particularly those in marginalized communities, face heightened risks during emergencies due to social and economic factors.
• Health and Safety Concerns: Disasters can exacerbate health issues for women, including reproductive health needs that are often overlooked in emergency responses.
• Stereotyping as Victims: Women are frequently portrayed primarily as victims rather than active participants in response efforts.

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Venn Diagram: Poster

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3. Rehabilitation Stage

• Economic Disempowerment: Women may face barriers to accessing resources for recovery, such as financial aid or employment opportunities.
• Social Roles and Responsibilities: The burden of caregiving responsibilities can hinder women’s ability to engage fully in rehabilitation processes.
• Inadequate Support Services: Rehabilitation efforts often lack gender-sensitive approaches that address the unique needs of women.

4. Reconstruction Stage

• Underrepresentation in Reconstruction Planning: Women are often underrepresented in decision-making roles regarding rebuilding efforts, leading to gender-blind policies.
• Access to Resources: Women may struggle to access land rights or property ownership, affecting their ability to rebuild their lives post-disaster.
• Sustainability Concerns: Gendered perspectives on sustainability and community needs may be overlooked in reconstruction plans.

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Overlapping Areas

In the overlapping areas of the Venn diagram, we can identify common gender biases that persist across multiple stages:

• Systemic Inequality: The overarching societal norms and structures that perpetuate gender inequalities affect all stages of disaster management.
• Limited Participation: Across all stages, women's participation is often limited due to cultural norms and stereotypes that dictate their roles.
• Access to Resources and Information: Women consistently face barriers in accessing critical resources and information necessary for effective disaster management.

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https://wrd.unwomen.org/sites/default/files/2022-07/Merged%20ESARO%20SF%20tools.pdf

https://www.facebook.com/MataAmritanandamayi/photos/ten-years-ago-in-the-aftermath-of-the-indian-ocean-tsunami-ammas-ashram-diverted/10152577965498302/

Case Studies (Brighter Picture)

• Amma and 2004 Tsunami: Collage of pictures of disaster relief efforts. https://www.amritapuri.org/on/tsunami2004 https://amma.org/news/the-2004-indian-ocean-tsunami-a-borderless-disaster-met-with-unbound-compassion/
• Major Sita Ashok Shelke: Bailey Bridge in the landslide-stricken Chooralmala village of Wayanad. https://www.hindustantimes.com/india-news/wayanad-landslides-why-did-major-sita-shelkes-photos-from-keralas-chooralmala-go-viral-bailey-bridge-101722661659463.html

Reports

• National Institute of Disaster Management: Gender and Disaster Management: TOT Module
• Sendai Framework: Gender Action Plan to Support Implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030
• GFDRR & World Bank: Gender Dimensions of Disaster Risk and Resilience
• UN Women: Checklist for Gender Equality and Social Inclusion in Disaster/Emergency Preparedness in the COVID-19 Context
• UN Women, UNICEF, UNDP: Gender Equality, Disability and Social Inclusion Mainstreaming in Disaster Risk Reduction
• IFRC: A practical guide to Gender-sensitive Approaches for Disaster Management

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Statistics, research and magazines

• Gender dynamics in disaster risk resilience and Gender Responsive Disaster Risk Reduction: https://www.undrr.org/implementing-sendai-framework/sendai-framework-action/gender https://www.undp.org/blog/women-are-hit-hardest-disasters-so-why-are-responses-too-often-gender-blind https://www.undrr.org/publication/policy-brief-gender-responsive-disaster-risk-reduction
• Ecofeminism : https://www.bustle.com/articles/155515-what-exactly-is-ecofeminism https://www.sciencedirect.com/science/article/abs/pii/S2212420920315284?via%3Dihub

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Space-Based Earth Observations for Disaster Risk Management - Scientific Figure on ResearchGate. Available from: https://www.researchgate.net/figure/Disaster-management-cycle_fig2_339835852 [accessed 7 Jan 2025]

#9 - Inclusive technology design for �social good

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Exploring principles and practices of inclusive tech design aimed at promoting social good
• Proposed topics cover the design of assistive technologies for women, gender-sensitive tech innovation in public services, �and the role of participatory design in addressing gender issues

#9 - Inclusive technology design for social good

Wall #1: Origins & Evolution

Theme Title: "From Origins to Opportunity: The Evolution of Inclusive Tech"�Banner Title: "Inclusive Tech Design for Social Good: A Journey through Technology and Humanity"

• Visuals & Infographic Timeline:
• Cognitive Revolution: Pioneers like Alan Turing and the analogy of the mind as a computer.
• Computationalism: Early algorithms and the rise of AI.
• History of Computer Science: Key milestones such as neural networks, machine learning, and Big Data.
• Visual Metaphors: A brain transforming into a computer, symbolizing how ideas shaped technological evolution.
• Interactive QR Code Scanners: Link to short videos on each milestone.

Interactive Element:

• "Discover & Reflect" Quiz:�Participants answer simple questions about historical tech milestones to unlock fun facts and gain insights.

Key Message:�"From the birth of computing to AI breakthroughs, the evolution of tech reflects both innovation and the embedding of human behaviors, practices, and biases."

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#9 - Inclusive technology design for social good

Wall #2: Connecting the Dots

Theme Title: "Bias in the Machine: From Patterns to Practices"

Section Titles and Explanations

1. "Spot the Source":�Focus: Selection Bias
• Explanation:�Selection bias occurs when the data collected for training an AI system is incomplete, imbalanced, or not representative of the real-world population.
• Example: Training an AI chatbot with only urban-centric language excludes rural expressions.
• Visual: A sieve filtering uneven-sized pebbles, symbolizing how non-representative data "filters out" diversity.
• Interactive Prompt:
• A thought bubble for visitors: "What happens when data excludes diverse voices?"
2. "Challenge the Lens":�Focus: Stereotyping
• Explanation:�Stereotyping bias arises when AI perpetuates common societal assumptions, such as gender roles or cultural clichés.
• Example: Job recommendation systems suggesting nursing roles predominantly to women.
• Visual: Clear vs. tinted glasses representing how stereotypes distort reality.
• Interactive Activity:
• A collaborative "word tree" where visitors complete prompts like "AI should be ______" to suggest ideal characteristics.
3. "Unmask the Impact":�Focus: Algorithmic Bias
• Explanation:�When biases in data and design go unchecked, they evolve into algorithmic bias, affecting outcomes in critical areas such as hiring, credit scoring, and law enforcement.
• Example: Facial recognition systems with higher error rates for darker skin tones.
• Visual: Flowchart connecting selection bias → stereotypes → algorithmic bias → real-world impact.
• Interactive Prompt:
• Visitors match real-world scenarios (e.g., hiring discrimination, unfair credit scoring) to the type of bias that may cause them.

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#9 - Inclusive technology design for social good

Wall #3: Real-World Reflections

Theme Title: "Experience, Express, Empower"

Interactive Chatbot Simulation:

• "Explore Everyday Bias":
1. Metro Ticket Bot: Gendered language.
2. Service Booking Bot: Gender roles.
3. Job Search Bot: Gender stereotypes in job recommendations.

Active Participation:

• Word Tree of AI Values:�Visitors write their thoughts or draw how they envision "Inclusive AI" on cards. These are hung on a collaborative "tree" symbolizing growth and shared understanding.

Key Message:�"AI should reflect humanity’s best values, not our blind spots. Let’s build tech that empowers everyone."

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Station #9 layout

Station Topic: Inclusive Technology Design for Social Good

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Bias Chosen: Algorithmic Bias It is when AI makes unfair decisions because of biased or incomplete training data.

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Establishing connection to Snake and Ladders Game

1. Snakes and Ladders originated as "Moksha Patam" in India, symbolizing the spiritual journey toward liberation.
2. Ladders represented virtues leading to progress, while snakes symbolized vices causing setbacks.
3. Rooted in scriptures like the Upanishads, the game taught the balance of karma and dharma in life.

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Wall #2

Center piece with QR code

Wall #1

Wall #3

Wall #1 Information - Station layout

Poster elements

Timeline of:

Computationalism

Cognitive Revolution

AI Revolution

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Role of Steve Jobs in bridging the gap between Tech and humanities

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All the positive developments are represented as ladders in Snake and Ladders

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QR code content

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Wall #1 - Content layout

Computationalism (1950s):�The idea that the mind functions like a computer, processing information through rules and algorithms.

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Cognitive Revolution (1960s-70s):�A shift in psychology to focus on understanding mental processes like thinking, memory, and perception, emphasizing the "mind" over behavior.

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Role of Steve Jobs (1980s-2010s):�Bridged technology and humanities, focusing on intuitive design and inclusive user experiences. His innovations made tech accessible and human-centric, paving the way for modern UX in AI.

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AI Revolution (2000s-Present):�The integration of AI in everyday life, transforming how we interact with technology, from automation to personalized user experiences.

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Poster design

Wall #2 - Station layout

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Poster elements

• Major hindrance in tech design: Algorithmic Bias

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• Explaining Algorithmic Bias with with infographics and example

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• Quick digital poster to show about Algorithmic Bias�

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Wall #2 - Content layout

Poster design

Algorithmic Bias

Algorithmic bias occurs when an AI or algorithm produces unfair, inaccurate, or prejudiced outcomes due to flawed design, unbalanced training data, or systemic assumptions.

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How Algorithmic Bias Affects Technology and Gender

1. Unequal Data Representation:
1. AI models trained on biased data often exclude women and minorities.
2. Reinforces Stereotypes:
• Algorithms may promote traditional gender roles, like women in caregiving jobs.
3. Reduces Usability:
• Tech like voice recognition often works better for men, marginalizing women.

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Algorithmic Bias: A Hindrance to Inclusivity

1. Blocks Equal Opportunities:
2. Bias in hiring and financial systems disadvantages women.
2. Excludes Diverse Needs:
• Biased AI fails to reflect the experiences of all users.
3. Amplifies Inequality:
• Algorithms can perpetuate and worsen existing societal biases.

Center piece elements

Wall #2

Center piece with QR code

Wall #1

Wall #3

Desk elements

Collage of various innovative AI products created

Game of snake and ladders with dice

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• Activity Showcasing and explaining the bias and then giving real life scenarios for participants to select the bias �

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Activity Example

Hiring Bias�Scenario: An AI hiring tool screens resumes for a software engineering position. It selects mostly male candidates because the training data was historically male-dominated.�Question:

• What caused the bias in the AI system?�a) Lack of female applicants�b) Historical data being male-dominated�c) Random selection�Answer: b) Historical data being male-dominated

Voice Recognition Bias�Scenario: A virtual assistant struggles to recognize commands from women but works seamlessly for male users.�Question:

• What is the primary reason for this bias?�a) Women's voices are harder to analyze�b) Training data primarily used male voices�c) The AI was designed to ignore gender�Answer: b) Training data primarily used male voices

Loan Approval Bias�Scenario: A bank's AI system denies more loans to women entrepreneurs than men because the training data included fewer women applicants.�Question:

• How can this bias be addressed?�a) Collect diverse and balanced data�b) Stop using AI for loan approvals�c) Increase the number of loans given�Answer: a) Collect diverse and balanced data

Poster design

#10 - Ethics, data science, and �social problem solving

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Investigating the ethical implications of data science and AI in gender contexts
• Discussions can include algorithmic bias, ethical AI development, data privacy concerns, and the use of data science to address �gender-specific social challenges

#10 - Ethics, data science, and social problem solving

Revealing biases through case studies:

🔹 Confirmation Bias(data science)�Amazon's AI recruitment tool showed bias against women because it was trained on resumes mostly from men. The system downgraded resumes with female-associated terms, reducing the chances of recommending women for leadership roles. Due to these biases, Amazon discontinued the tool.

The AI system was trained on historical resumes, which were predominantly from men, reflecting a male-dominated job market in leadership and technical roles. This historical trend acts as the "confirmation" of a biased notion that men are more suited for these men roles.

🔹 Hindsight Bias(social policy)�Neglect of paid family leave and childcare. For years, women's unpaid labor in caregiving was undervalued, based on the belief that it was a natural responsibility for women. This gender bias ignored the need for societal support for working mothers.As more women entered the workforce, the lack of support became more evident. However, hindsight bias made it seem like the need for family leave and childcare “should have been obvious” all along, ignoring the cultural norms that previously prevented these policies from being considered. This oversimplifies the issue and overlooks the gendered assumptions that delayed action.

• The bias glosses over the fact that these gendered assumptions—about women’s primary role as caregivers—were deeply embedded in societal structures. The delay in implementing supportive policies was not just due to oversight, but also because of long-held beliefs that women, rather than society, should bear the burden of caregiving.

🔹 Intersectional Bias(ethics)�Amazon's facial recognition tool, Rekognition, struggles to identify darker-skinned individuals accurately, especially women. It often misclassifies them or shows low confidence in results. This raises ethical concerns, especially if used by law enforcement, as it could lead to discrimination or wrongful arrests. Critics also point to Amazon's lack of transparency about Rekognition’s algorithms.

• When an AI system is trained on data that does not represent diverse populations, it tends to be less effective at recognizing people outside of that demographic, resulting in disparate accuracy rates based on skin tone and gender.

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LAYOUT

Key Gender Stereotypes

Societal relevance

Activity: "Bias Detective"

Objective: Spot and reflect on hidden biases in decision-making.

Setup:

1. Create fictional resumes:� Prepare a set of 8–10 short, fictional resumes. Use subtle hints about gender, such as names (e.g., Alex, Emma), pronouns, or activities (e.g., “captain of the women’s soccer team”). Ensure resumes have similar qualifications but vary in gendered language.�
2. Introduce the Game:�
• Frame it as a talent scout game. The participants are “hiring detectives” tasked with identifying the best candidates based on predefined criteria (e.g., experience, education, achievements).
• Give a strict time limit (e.g., 5 minutes) to shortlist their top 3 candidates.
• Award "points" for how closely participants follow the criteria.
• Track their decisions to identify patterns (e.g., frequent selection of male-associated terms)

3. Execution:

• In groups, participants discuss and collectively decide on the top 3 candidates.
• Observe whether biases shift with group dynamics.

Debrief:

1. Reveal the Twist:
• Display a summary of the resumes and highlight the subtle gendered cues (e.g., male vs. female-associated language).
• Share anonymized results, showing any trends in bias (e.g., more participants selecting resumes with male-associated terms).
2. Facilitate a Reflection:�Ask questions like:
• “What influenced your decisions the most?”
• “Did you notice the gendered hints?”
• “How might algorithms trained on biased data perpetuate similar patterns?”
3. Discuss Solutions:�
• Brainstorm ways to minimize bias in decision-making, such as using anonymized resumes or standardized scoring criteria.

Activity: “Bias Bingo”

1. Setup the Bingo Card:�Create a 5x5 grid with bias-related statements, such as:
• Assumes traditional gender roles.
• Overlooks systemic barriers.
• Relies on unpaid caregiving as a default.
• Ignores the economic value of caregiving.
• Uses hindsight to oversimplify.
2. Present the Case Study in Segments:
• Segment 1: "In the past, caregiving was viewed as a natural responsibility for women, undervaluing their unpaid labor."
• Segment 2: "Policies like paid family leave were not considered necessary because of cultural norms that assumed women stayed at home."
• Segment 3: "As women entered the workforce, the lack of support became a growing issue."
• Segment 4: "Modern critiques say the need for these policies 'should have been obvious' all along, oversimplifying the cultural barriers of the time."
3. Tie Statements to the Bingo Card:
• After reading each segment, give participants time to mark the relevant biases they recognize on their bingo cards.
4. Facilitate a Discussion:�Once the game ends (e.g., someone gets bingo), ask participants:
• “What biases did you spot in the case study?”
• “How do these biases still show up in modern-day discussions about family leave?”

Activity: "Snap Judgment"

Objective: Highlight unconscious biases in identifying traits in faces.

Setup:

1. Present a set of images on a chart:
• Show 6–8 individual faces with diverse combinations of gender, skin tone, and expressions.
2. Traits to Judge:
• Ask participants to assign a quick label to each face based on one of these traits:
• Emotion (e.g., happy, angry, neutral).
• Confidence level (e.g., confident, unsure).
• Approachability (e.g., approachable, unapproachable).
3. Add a Time Limit:
• Give participants 3–5 seconds per face to encourage snap judgments.

Execution: Participants write their quick impressions on a sticky notes and place them accordingly

Debrief:

• Initiate a discussion, focusing on trends like:
• Are certain genders consistently rated more “confident”?
• Are specific skin tones associated with particular emotions?

Reveal the Patterns:

• Highlight discrepancies in perceptions based on gender or skin tone.
• Ask: “Why might we associate certain traits with specific appearances?”

Discuss the Impact:

• Link the activity to real-world implications(amazon’s facial recognition tool)

#11 - Emerging technologies: �opportunities and vulnerabilities

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Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Evaluating the opportunities and vulnerabilities that emerging technologies present for gender equity
• Proposed topics can include the benefits and risks of blockchain for women’s financial inclusion, the gendered impacts of �5G and 6G technologies, and the potential for VR and AR to create inclusive virtual spaces

#11 - Emerging technologies: �opportunities and vulnerabilities

Detailed overview of planned activities - Marble Ramp Race

Activity Walkthrough: 3–4 minutes

Objective: to help participants recognize their own biases when assigning accessibility to the tech�

Participants will choose to race as 'men' or 'women’ or one person will roll the marbles together on two parallel tracks to see which one wins and goes faster. Both tracks represent the road to engaging with emerging technologies, but they aren’t equal. The men’s track representing challenges like competition or resource access.

In contrast, the women’s track features speed breakers or odd obstacles, each tied to specific challenges:

• For 5G/6G, highlighting only successful entrepreneurs while ignoring the struggles of the rest . “Lack of mentor” SURVIVORSHIP BIAS
• In AR/VR, there’s underrepresentation in design, stereotyping, and access barriers. “ar/vr headset/glasses lead to discomfort in women, design not informed on female physiology” HALO EFFECT
• In Blockchain, challenges include exclusion from decision-making and the male-dominated culture. “Lack of funding to female blockchain startups” ANCHORING BIAS

Each speedbreaker will have a signboard pointing the challenge, along with a description in next poster connecting it to one of the three biases, explaining the challenges in emerging tech. Participants will see firsthand how these biases create unequal experiences, even within the same technology.

Resources Required: �2 Marbles �High quality cardboard �Sticky notes �2 posters �����

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Station #11 Layout

POSTER 1 -

Speed Breakers of Thought: Navigating Cognitive Biases

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A poster connecting speed breakers to biases (analogy).

This will connect the poster to the activity, giving a smooth transition.

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Table -

ACTIVITY: Pace Breakers

Marble ramp & race

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Poster 2 - �Access Race: Are We All at the Start Line ?

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• A poster connecting biases to emerging technology
• Ways to overcome Biases

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• Sticky Notes

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Table with Marble Ramp

Poster 1 - Speed Breakers of Thought: Navigating Cognitive Biases -

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Speed Breakers of Thought: Navigating Cognitive Biases 🚧💭

Emerging Technologies do not Include Gender-Neutral Roads

Women in tech often face "speed breakers" — subtle but impactful challenges rooted in cognitive biases. Just like speed breakers slow vehicles on a smooth road, biases in design of technology lead to challenges, disrupting the momentum of progress for women navigating the field of emerging technologies.

3 Cognitive Speed Breakers in Focus:

1. Survivorship Bias

When we focus on people, things, or data that have "survived" or succeeded in a particular process while ignoring those that have failed or been excluded. Here, designing for those already using emerging technology, excluding marginalised genders.

2. Anchoring Bias

Individuals rely too heavily on the first piece of information (the "anchor") they receive when making decisions, even if that info. is irrelevant or arbitrary. Here, gender serves as an anchor in decision making.

3. Halo Effect

Our overall impression of a person or thing influences our judgments about their specific traits. If we have a positive impression of someone, we tend to assume they have other positive qualities. Here, assuming success in one domain/ gender applies to all genders.

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Take part in our interactive Pace Breakers - Marble Ramp activity to see how these biases create challenges

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Table - Activity: Pace-breakers Marble Ramp

Signboard Content

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• Constantly adapt to new advancements

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• Steep Learning Curve to gain Expertise in using

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• Lack of funding
• Exclusion from Decision-Making�(Blockchain) (Anchoring bias)

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• Limited opportunities for women in research and development
• Lack of mentors

(5G/6G technology) ( Survivorship bias)

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• Cyber sickness and discomfort
• Hardware designed according to male physiology�(AR/VR Tech) (Halo effect)

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MEN

WOMEN

Poster 2 - Access Race: Are We All at the Start Line ?

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• highlighting only successful women in technology
• Limited opportunities for women in research and development
• Lack of mentorship programs

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• VR equipment is predominantly designed
• for male physiology
• Women are more than twice as likely to experience motion sickness in VR

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• <10% of VC funding goes to female-founded crypto startups
• Women earn 46% less in blockchain roles

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• Only 26.7% of technology positions are held by women
• Women represent <15% of workforce in telecom R&D
• 66% of women see no clear career advancement path

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• Only 15% women occupy leadership positions
• · 8% in C-suite/boardroom positions

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• 90% of blockchain funding supports male-led projects
• Bitcoin community composition: 85.77% men

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Overcoming Bias : Ask yourself what

data didn’t “survive,” from an event, or dataset you are using?

Overcoming Challenge :

• Focused on increasing diversity and visibility in telecommunications
• Aims to highlight hidden voices in 6G technology

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Overcoming Bias : Avoid generalizing from single characteristics and expose yourself to diverse perspectives

Overcoming Challenge :

• Develop sex-sensitive and gender-sensitive virtual environments
• Include diverse user groups in prototype testing and development

Overcoming Bias : take a step back and examine the Anchors and look at data

Overcoming Challenge :

• Understand the Anchor- “ Male-Dominated Narrative
• Highlight Female and Non-Binary Innovators

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}

SURVIVORSHIP BIAS in

5G/6G

}

HALO EFFECT

in

AR/VR TECH

}

ANCHOR

BIAS

in

BLOCKCHAIN

Board - Sticky notes

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Direct visitors -

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Put up ways to make emerging technology unbiased and more inclusive

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Resources -

Pen / marker

Sticky notes

RESOURCES REQUIRED

ACTIVITY - MARBLE RAMP

• High quality cardboard - ramp and signboards
• 2 marbles
• centre table
• straws
• double sided tape
• markers

POSTER

• poster 1 INTRODUCTION TO BIASES
• poster 2 CONNECTING THE BIASES TO EMERGING TECH
• poster 3 STATISTICS

BOARD

• a board
• sticky notes��

#12 - Gender and finance: technological innovations for financial inclusion

Scope (As per update on website regarding the conference)

https://www.amrita.edu/events/gender-technology-conference-2025/)

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• Examining the impact of financial technologies (FinTech) on gender equity
• Proposed topics include the role of blockchain and digital banking in promoting women's financial inclusion, gender-sensitive investment strategies, and the use of data analytics to address gender disparities in financial services

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Station #12 layout

Wall #2

Center piece with QR code

Wall #1

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Wall #3

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Station Topic: Gender and finance: technological innovations for financial inclusion

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Biases Chosen:

• Access bias - unequal availability of opportunities or resources.
• Inclusivity bias - failure to consider or include diverse perspectives and needs.
• Default Male Bias - tendency to assume male perspectives, characteristics, or roles as the norm in various contexts, often unconsciously.

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Activities:

1. A survey to understand whether gender bias impacts accessibility and inclusivity of financial tools among the hackathon participants

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• Participants would be given a statement (eg: "Imagine a person using an advanced investment app"). They would then be asked whether they initially thought of a man, a woman or neither. To know how societal stereotypes affect assumptions in matters regarding finance.

Inclusivity Bias

Access Bias

Default Male Bias

Center piece elements

Wall #2

Center piece with QR code

Wall #1

Wall #3

Desk elements

Copies/printouts of foreign currencies to showcase the ratio of females to males depicted in currency notes (only 15% of world currencies have women on them)

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(Activity Elements)

OR Code for survey

Sticky notes for participant's to write their opinion on statements

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QR code content

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QR code content

• A survey to understand whether gender bias impacts accessibility and inclusivity of financial tools among the hackathon participants

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#12 - Gender and finance: technological innovations for financial inclusion

Detailed overview of planned activity

• Explain the bias in detail through face-to-face interaction and also with the help of posters.

Activity 1:

• Participants will be asked to fill a survey (through QR code) to gather insights into how gender bias impacts the accessibility and inclusivity of financial tools for individuals of all genders
• The data collected will be visualized as a chart once ‘n’ number of responses are collected from the participants (eg: 20 participants). The chart will be updated as the survey sample reaches multiples of ‘n’ (eg: 40, 60, 80..)

Activity 2:

• Participants would be presented with statements regarding people dealing with financial matters. They will be asked whether they initially thought of a man, a woman, or neither. How societal stereotypes might shape these assumptions will be discussed with the individual participants and they would be asked to write down their thoughts on sticky notes which would be posted on a wall of the stall.

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Resources required

• Posters detailing the bias with real-life examples
• QR code for survey
• Sticky notes for participant's to write their opinion on statements regarding gender bias in financial matters
• Board to paste the sticky notes so that participants can see other peoples views on the gender bias
• Copies/printouts of foreign currencies to showcase the ratio of females to males depicted in currency notes

Access bias - unequal availability of opportunities or resources.

Access bias refers to inequalities that arise when certain groups of people face barriers to obtaining or utilizing resources, opportunities, or services. These barriers may stem from factors like socioeconomic status, geography, language, gender, or technological disparities.

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Key Concept

• Barriers: Obstacles or hindrances that prevent individuals or groups from accessing resources, opportunities, or services.
• Inequalities: Disparities or imbalances that occur when certain groups have less access to resources or opportunities compared to others.
• Factors influencing barriers: Underlying reasons why barriers exist, eg:socioeconomic status, language, gender, or technological disparities.

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Real-World Example: Access to Credit and Investment Tools

• Traditional Credit Scoring Bias: Credit scoring -> formal employment history or property ownership = Women being denied access to loans or offered loans at higher interest rates, even when they are capable of repayment.
• Gender Data Gap in Financial Tech (FinTech): Datasets that underrepresent women = tools and algorithms that are less optimized for women's financial behavior. Eg: budgeting apps may fail to consider expenses unique to women (e.g., caregiving costs), or investment platforms may overlook the preferences women often express for lower-risk strategies.

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Consequences of Access Bias

• Limited Financial Independence: Women may struggle to access credit to start businesses, invest in education, or purchase property.
• Reinforced Economic Inequality: The lack of access to financial tools perpetuates the economic gap between genders.

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How to Break the Bias

• Gender-Inclusive Financial Tools: Specifically designed for women, such as microloans for female entrepreneurs or investment platforms focusing on women's financial goals.
• Improved Data Representation: Include more diverse datasets to better tailor their products to women's needs.

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Inclusivity bias - failure to consider or include diverse perspectives and needs

Inclusivity bias occurs when systems or decision-making processes fail to adequately account for the diversity of the populations they serve, leading to the underrepresentation of certain groups. This bias can stem from a narrow perspective that assumes one-size-fits-all solutions, overlooking the unique needs, experiences, or preferences of different demographic groups.

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Key Concept

• Populations are inherently diverse -> cultural, social, economic, and demographic characteristics. Inclusivity bias = systems fail to account for this diversity, leading to exclusion or marginalization.
• One-size-fits-all solutions - approaches designed with the assumption that all users or groups have the same needs, resulting in unequal access or outcomes.
• Marginalization refers to the exclusion or sidelining of certain groups, either intentionally or unintentionally = groups left with fewer opportunities.

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Real-World Example: Women’s Investment Needs Overlooked by Financial Platforms

• Financial tools, apps, and services are designed with assumptions based on male-dominated financial behaviors = unintentionally marginalize women.
• Investment platforms often emphasize high-risk, high-return strategies, assuming users prioritize aggressive financial growth. Research shows that women tend to favor lower-risk, long-term investment strategies, often prioritizing financial stability over speculative growth.
• Financial tools often fail to address unique challenges faced by women, such as career breaks for caregiving or the gender pay gap.

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Consequences of Inclusivity Bias

• These platforms may unintentionally alienate women by not offering tools aligned with their financial goals -> do not reflect their lived experiences.

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How to Break the Bias

• Create tools tailored to diverse financial behaviors and goals, such as savings programs for caregivers or low-risk investment portfolios.
• Engage women directly in the development process to ensure their needs and preferences are met.

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Default Male Bias- financial products designed predominantly for male users base

Default male bias refers to the tendency to assume or prioritize male perspectives, characteristics, or roles as the norm or standard in various contexts, often unconsciously.

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Key Concept

• Assumption that male perspectives are the standard or norm.
• This bias often operates unconsciously, leading to the marginalization or underrepresentation of other genders. The impact of this bias can be seen in various domains, such as language, workplace dynamics, media representation, product design, and medical research.
• By assuming male as the default, this bias perpetuates stereotypes and systemic inequalities

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Real-World Example: Why Women are in Debt?

• Gender pay gap - women earned 15.5% less than men in 2020, making them more vulnerable to financial difficulties.
• Motherhood often leads to career gaps and lower pay for women - single mothers facing significant financial challenges due to low savings and arrears on bills or credit.

Around 90% of single parents are women, and many lack child maintenance payments, increasing their struggle with debt.

• Women are more likely to use credit for necessities and are targeted by Buy Now Pay Later schemes, which encourage unnecessary spending and casual debt.
• Financial abuse, a form of domestic abuse, often involves women losing control of their finances, with 7.9% of UK women affected. Abusers may force partners to stop working, take their wages, take out loans in their names, or put bills in their names, making them liable for unpaid debts.

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Consequences of Default Male Bias

• Marginalization of women in various sectors, such as leadership roles
• Biased medical research that neglects women's health needs.
• Glass ceiling effect - lack of female representation in positions like chairperson, executive officer, president, etc, in financial sector MNCs. Just over 10% of Fortune 500 companies had women in CEO positions.

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How to Break the Bias

• Diverse representation and inclusion of women in all areas, including leadership roles and decision-making processes.
• Implement and enforce policies that address and counteract systemic biases, fostering an environment of awareness and fairness.

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Sticky notes will provide details of the graphs.

The Awakening of Universal Motherhood

An Address given by Amma on the occasion of the Global Peace Initiative of Women Religious and Spiritual Leaders, at Palais des Nations, Geneva, on October 7th, 2002.

Recognize the inherent value of women: Amma emphasizes that women are not inferior to men in any way and possess unique strengths and capabilities. This recognition is fundamental for the financial sector, which should actively seek to promote women into leadership positions and value their contributions

Challenge traditional gender roles: Societal norms and customs have historically limited women's opportunities and potential. In the financial sector, this means actively working to dismantle traditional gender roles that may prevent women from rising to their full potential

Promote equal access and opportunity: Amma argues for equal status and opportunity for women. Financial institutions should actively work towards equal pay, eliminate discriminatory practices in hiring and promotion, and ensure women have access to financial resources and services as men.

Cultivate inner strength and break free from limitations: Amma uses the metaphor of the elephant to explain how women’s minds have been conditioned to accept limitations. The financial sector should encourage women to develop their inner strength, challenge their self-imposed limitations, and take an active role in shaping their careers

Prioritize education and empowerment: Lack of education is a barrier for women. The financial sector should actively support and invest in initiatives that provide financial education to women, helping them to become more empowered economic actors and leaders. This includes mentorship and leadership training

Address systemic issues: Deeply rooted issues like the dowry system, female foeticide, and child trafficking have to be addressed. Issues of equality have to be dealt with systemically within the financial sector as well

Encourage men to embrace the feminine: Men need to recognize and develop their feminine qualities like empathy and understanding. This change of mindset can lead to greater cooperation and mutual respect between men and women in the workplace, leading to better decision-making and a healthier work environment

Promote the language of the heart: Amma distinguishes between the language of the intellect (aggressive, ego-driven) and the language of the heart (compassionate, service-oriented). The financial sector could foster a culture that emphasizes the language of the heart, fostering collaboration, and care for the customers from any background

CASE STUDY

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Self-help groups developed by Ammachi Labs to show how Amrita is promoting financial independence and empowerment among rural women

Virtual Reality (VR) Station – Exit

Updates

VR Scene #2: “In a leftie’s world”

Scene 1: The participant first enters into a world where the proportion of right-dominant people to left dominant people is 9:1. They are given a morning routine scenario where they are made to open doors, use scissors, made to read a newspaper, scroll your phone and have your breakfast. Flash forward to a classroom scenario where you have two options of places to sit; right-based arm desks and a common desk and bench that you will be sharing with 2+ people. You are also encouraged to write something on the board.

Scene 2: The proportion of right-left dominant people are reversed now, and it's a left dominant world. The same scenarios are played again, but with a twist; everything is left-friendly: door-knobs on the right side of the door, text being written from right to left etc. You are not supposed to eat with your right-hand as this considered as unhygienic. All the buttons (power, volume button, fingerprint sensor) is on the left-side of your phone. You can only use your left fingers to unlock your phone as the phone is unable to read right fingerprints. All the hand emojis you use only show left-hand (🫡🥱👌🏻etc.). Virtual keyboards are designed with left-handed typing in mind, with common punctuation marks, delete buttons, and special characters easily accessible to the left thumb. The classroom only has left-armed desks or you are supposed to share the common desks with left-handed people whose elbows always bump against yours. You are supposed to write from right to left using a pen, causing ink smudges as you write along.

Others??

Updates

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The beginning ☺