“As long as there are slaughterhouses there will be battlefields.” Leo Tolstoy (1828-1910)

The technical and commercial viability of an animal communication translation mobile app.

Introduction.

This research will aim to assess advances in animal communication and behaviour translational research within the context of business management. Firstly, the research will analyse the technical viability of an animal communication translation application (for example, examining the advances that have taken place and are currently taking place in this field). Secondly, the research will aim to examine the commercial viability and route to market for a mobile application for animal communication translation.

Aims

To provide insights into the technical viability of a mobile application for animal communication/behaviour translation.

Discuss the commercial viability and route to market for a mobile application for animal communication and behaviour translation.

Research questions.

Is a mobile application to help with animal communication translation technically possible?

What is the commercial viability and route to market for a mobile application for animal communication translation?

Research Approach

The conceptual framework and theoretical underpinning of the research is from an ontological position of a pragmatist perspective and view of knowledge, for example with a commitment to uncertainty, and an acknowledgement that any knowledge is relative and not absolute. This approach is based on the view that reality is continuously questioned, negotiated and interpreted. Qualitative and quantitative methods are often combined in research with a pragmatic approach (Johnson & Onwuegbuzie, 2006); this is something that this research aims to achieve; for example, through using statistics alongside qualitative interviews. The epistemological stance of the research is aligned to the pragmatist objective to produce socially useful knowledge. This research aims to examine a socially useful mobile application with understanding that current realities are constantly renegotiated.

Literature Review

The literature review is divided into two main parts, the first focussing on the technical the second focussing on the commercial. There have been significant advances in the ability of computer science to provide translation (Y LeCun et al 2015). There has also been significant advancements in the data set available to analyse animal communication and behaviour; for example the widespread use of Youtube for uploading video recordings featuring animals on the internet (see Gill et al 2007).

Discussing the recent studies in animal communication, John Placer & C.N. Slobodchikoff (2001) developed metrics for decoding animal audio using automated computing, which enabled audio analysis based on identifying particular categories to decode animal communication in prairie dogs. One of the important aspects the research by Placer and Slobodchikoff (2001) is that using automated methods were used and reduced the inconsistencies in results caused by variances in human interpretation. Another important aspect about the automation was it allowed for increased speed of the categorisation of the audio analysis whilst at the same time improving accuracy.

Later research by Herzing (2006) worked with underwater video which included audio input and was able to capture contextually sensitive information in relation to dolphin communication. Herzing 2006 identified important aspects relating to dolphin communication such as gestures, vocalizations, gaze, body and head orientation. The importance of this study was that it demonstrated further potential of measuring animal communication in contextual, real-time interactions, and through changes over time. Therefore this highlights the ability of computer science to further advance this area of study.

There has been a range of groundbreaking research in ape communication and behaviour, ‘Modern technology has contributed greatly to the study of ape cognition’ (Wasserman & Zentall, 2006). An example of one of these ground breaking discoveries was when Kanzi an ape who had observed his mother in language lessons and was raised in a language-rich environment spontaneously used the computer picture keyboard to combine symbols and communicate with the researcher. Via observational learning, Kanzi has demonstrated more understanding of spoken English under controlled conditions than any other non-human animal in history. He understood almost 600 sentences that he had never heard before.

A currently ongoing project that started at the University of Nottingham in 2015 is, HABIT (Horse Automated Behaviour Identification Tool), an Animal Computer Interaction (ACI) project that aims to further research in equitation science and computer science. HABIT research proposes automated analysis and recognition of horse-to-horse and horse to-human behaviours, as observed in video. A video dataset is being compiled. The system is being developed to automatically recognise behaviours and their meaning.

From a commercial viability perspective there is a growing consensus that there is much more to be understood and learnt from animals and that they should no longer be treated as a wholesale commodity for consumption. For example in 2016 Google Trends showed a 90% increase in ‘vegan’ searches in last 12 months (veganfoodandliving.com). This demonstrates a strong interest around issues surrounding how animals are treated.

The value of the mobile application market is currently strong and growing. For example, the estimated global mobile app market revenue is predicted to be $75 billion in 2017 (Kim et al 2016). Currently, there are six popular app monetization models: direct sales, freemium, subscription, in-app purchases, sponsorship and crowdfunding. The insights below help inform the research discussion around potential revenue streams for a live mobile application for an animal communication translation.

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The cost of developing an app can range anywhere between £50,000 to over £1 million (savvyapps.com). Stated in research by Kumar et al 2016, before developing a mobile application there must be a precise cause defined to generate one. Therefore it is important that scope and criteria of an initial market version of the mobile application is defined. There is the ability with mobile applications to provide improvements via updates at any stage to the user however it is important to define the aims of an initial market ready application.

Proposed research methods

The secondary research will draw upon books, journals, reports, studies, databases and statistics, Examples of sources of statistics that this research will draw upon are; the Mintel market research database and Google trends.

Primary research will draw upon dialogue from relevant research groups (for example, ACI Animal communication institute, associated with the Open University) and researchers. For example, the researchers will be approached via email or Linkedin with the aim of inviting qualitative dialogue about their research experiences and perceived challenges. If there is opportunity to interview relevant researchers, Interviews will be recorded, transcribed and the data categorised for analysis. After the interview the researcher will reflect on the dialogue. The proposed sample size for researchers and relevant research groups is between five and fifteen interviews. This is to ensure the research timescale and scope remain manageable. By analysing data qualitative rather than relying on quantitative data to investigate the research questions, the data gathered will hopefully provide insight into beliefs, values, feelings, and motivations of those that interviewed.

The research will also aim experiment with the use of the innovative online platform Quora to ask relevant questions in the research area and encourage discussion from people interested in the subject area. ‘Quora provides opportunities for students to evaluate the credibility of the person answering the question, as well as the validity and accuracy of the arguments’. (Petty & Cacioppo, 1986).

Data Analysis

According to Basit (2003), data analysis is a crucial aspect of qualitative research. The dialogue with researchers via email, messages and forums and Quora, will draw upon discourse analysis techniques to identify themes, topics and keywords recurrent in the dialogues (Saunders et al. 2009). This will identify issues relating to the technical and commercial viability of a mobile application for animal communication. The research will however address issues raised by the dialogue regardless of the frequency of occurrence in coding and aim to mitigate the fragmentation of data which can result in a loss of narrative flow (Coffey & Atkinson, 1996). The bulk of the data analysis may be described as thematic analysis using coding to to identify patterns and contrasts.

Consent and potential issues.

Consent to proceed with the research will be sought from the organisation and from individuals invited to participate. The researchers and participants interviewed will be given the option of whether to be cited or to remain anonymous for reasons of confidentiality.

As with any research methodology there are limitations and “problems with this design arise largely from difficulties with interpretation.” (Brewerton and Millward, 2001, p .53), i.e. the analysis of data relies on the researcher's interpretation of what is said.

Research Timetable

June 2017

Topic decision and review of literature.

July 2017

Research proposal.

August 2017 - February 2018

Literature review and qualitative interviews with researchers and relevant groups.

February 2018 onwards.

Analysis followed by finalising dissertation.        

References.

Atkinson, P., Delamont, S. and Coffey, A. (2004). Key themes in qualitative research: Continuities and changes, Rowman Altamira.

Basit, T. (2003). 'Manual or electronic? The role of coding in qualitative data analysis', Educational research, 45(2), pp. 143-154.

Feilzer, M. (2010). 'Doing mixed methods research pragmatically: Implications for the rediscovery of pragmatism as a research paradigm', Journal of mixed methods research, 4(1), pp. 6-16.

Freberg, K. and Freberg, L. (2012). 'Incorporating Social Media in Teaching and in Research', Essays from E-xcellence in Teaching Volume XII, pp. 28.

Gill, P., Arlitt, M., Li, Z. and Mahanti, A. (2007). 'Youtube traffic characterization: a view from the edge'. Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, .

Hauser, M. D., Chomsky, N. and Fitch, W. T. (2002). 'The faculty of language: what is it, who has it, and how did it evolve?', Science (New York, N.Y.), 298(5598), pp. 1569-1579.

Herzing, D. L. (2006). 'The currency of cognition: Assessing tools, techniques, and media for complex behavioral analysis', Aquatic Mammals, 32(4), pp. 544.

Herzing, D. L., Delfour, F. and Pack, A. A. (2012). 'Responses of human-habituated wild atlantic spotted dolphins to play behaviors using a two-way human/dolphin interface', International Journal of Comparative Psychology, 25(2).

Kumar, N. A., Krishna, K. H. and Manjula, R. (2016). 'Challenges and Best Practices in Mobile Application Development', Imperial Journal of Interdisciplinary Research, 2(12).

Kim, H., Kankanhalli, A. and Lee, H. (2016). 'Investigating decision factors in mobile application purchase: A mixed-methods approach', Information & Management, 53(6), pp. 727-739.

Kohlsdorf, D., Herzing, D. and Starner, T. (2016). 'Method for discovering models of behavior: A case study with wild Atlantic spotted dolphins', Animal Behavior and Cognition, 3(4), pp. 265-287.

LeCun, Y., Bengio, Y. and Hinton, G. (2015). 'Deep learning', Nature, 521(7553), pp. 436-444.

North, S. (2016). 'Do Androids dream of electric steeds?: the allure of horse-computer interaction', interactions, 23(2), pp. 50-53.

North, S. (2016). 'Give me poetical science: an invited speaker abstract for RM4ACI (Research Methods in ACI) workshop',

North, S., Hall, C., Roshier, A.L. and Mancini, C. (2015). 'HABIT: Horse automated behaviour identification tool: A position paper'..

Palaiologou, I., Needham, D. and Male, T. (2015). Doing Research in Education: Theory and Practice, Sage.

Placer, J. and Slobodchikoff, C. (2000). 'A fuzzy-neural system for identification of species-specific alarm calls of Gunnison's prairie dogs', Behavioural processes, 52(1), pp. 1-9.

Placer, J. and Slobodchikoff, C. (2001). 'Developing new metrics for the investigation of animal vocalizations', Intelligent Automation & Soft Computing, 7(4), pp. 249-258.

Saunders, M. N. and Lewis, P. (2012). Doing research in business & management: An essential guide to planning your project, Pearson.

Slobodchikoff, C. and Placer, J. (2006). 'Acoustic structures in the alarm calls of Gunnison’s prairie dogs', The Journal of the Acoustical Society of America, 119(5), pp. 3153-3160.

Slobodchikoff, C. N. (2002). 'Cognition and communication in prairie dogs', The cognitive animal, pp. 257-264.

Online References.

http://www.veganfoodandliving.com/google-trends-shows-90-increase-in-vegan-searches-in-2016/

https://medium.com/@sm_app_intel/mobile-app-industry-revenue-statistics-wheres-the-money-come-from-82581a45186d

https://savvyapps.com/blog/how-much-does-app-cost-massive-review-pricing-budget-considerations