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PROBLEMS FROM AI
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TimeframeLevel 1: Technical Failures (AI Issues)Level 2: Misuse of Software (Security & Privacy)Level 3: Social Externalities (Societal Impact)Level 4: Software Behaves Badly (Quality & Stability)
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Today- AI hallucinations cause confusion
- Slow speeds affect usability
- Prompt injection causes security risks		- Bad actors use AI to spread misinformation
- Weak AI security enables identity theft		- Human artists aren't paid for AI art
- Some professions suffer labor shocks
- AI software includes biases		- Technologies like AutoGPT malfunction
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Medium Term- Opaque AI systems mislead users
- AI system reliability is questionable
- AIs hallucinate and remain exploitable		- Deepfakes pose social & political risks
- Next-generation AIs bring more cyberattacks
- AI fuels misinformation campaigns
- ChaosGPT comes online		- AI causes widespread job displacement
- Unequal AI access widens digital divide
- AI "counterfeit people" cause social chaos
- AI malfunctions cause the equivalent of a flash crash
- AI agents overwhelm existing systems
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Long Term- AI software faults are difficult to diagnose
- Autonomous AI malfunctions cause catastrophes
- Increasingly complex AI systems are harder to control		- AI enables bad actors to gain power
- AI-enhanced surveillance erodes privacy and civil liberties
- AI systems become weaponized, creating new forms of conflict		- Humans become totally dependent on AI ("WALL-E" scenario)
- Human autonomy gives way to AI decision-making
- AI algorithms make important societal decisions, raising governance issues		- Superintelligent AIs cause unintended consequences
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TECHNOLOGICAL AND REGULATORY SOLUTIONS
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TimeframeLevel 1: Technical Failures (AI Issues)Level 2: Misuse of Software (Security & Privacy)Level 3: Social Externalities (Societal Impact)Level 4: Software Behaves Badly (Quality & Stability)
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TodayTechnological:
- Reduce AI hallucinations, context lengths, latency
- Develop countermeasures against prompt injection

Regulatory:
- Limit AI usage in high-risk areas		Technological:
- Implement more secure ID verification methods
- Check authenticity for posts

Regulatory:
- Implement "Chips Act" and similar measure to discourage bad actors		Technological:
- Implement bias & provenance checks

Regulatory:
- Bolster intellectual property law, including for training data
- Educate public about GPT's limitations		Technological:
- Test software capabilities before releasing models
- Open source and deploys to identify boundaries of potential
- Implement checks and balances
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Medium TermTechnological:
- Monitor and manage AI unpredictability
- Redundancy and backup systems
- Improve AI system stability and reliability

Regulatory:
- Create standards for AI reliability
- Create sector-specific usage guidelines in coordination with industry		Technological:
- Build deepfake-detection systems
- Strengthen AI security measures
- Build countermeasures against AI-powered misinformation campaigns

Regulatory:
- Draft laws regulating deepfakes
- Strengthen cybersecurity standards		Technological:
- Create new jobs through AI technologies
- Make AI more accessible for everyone
- Build specific tech to prove provenance of all information

Regulatory:
- Support workers displaced by automation
- Enshrine equal access to AI technologies
- Create policies to mitigate AI-driven social inequality
- Create policies to ensure AI systems consistently self-identify		Technological:
- Strengthen observation/management of AI's emergent properties
- Create agents that won't lose their goals through time
- Build resilient systems to withstand high-volume DDOS-style attacks from autonomous entities

Regulatory:
- Create policies for AI misalignment and unforeseen behaviors
- Create laws to deal with autonomous agents
- Regulate licensing to create new AIs of similar calibre
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Long TermTechnological:
- Develop advanced AI interpretability techniques
- Implement high levels of checks and balances from known sources
- Implement autonomous error correction and self-healing in AI
- Develop control and predictability measures for complex AI systems

Regulatory:		Technological:
- Build advanced security measures
- Develop similarly powerful privacy technologies for individual data protection
- Implement private-only AIs to interface with others
- Set hard limits against AI weaponization

Regulatory:
- Balance AI deployment licenses
- Develop privacy regulations in AI surveillance
- Create policies regulation AI weaponization		Technological:
- Guide AI to operate in harmony with human society (broader goal alignment)
- Help people better integrate with AIs

Regulatory:
- Create measures to preserve human autonomy in decision-making
- Manage human dependency on AI with backups and reslience-building
- Create governance frameworks for AI decision-making		Technological:
- Develop advanced AI alignment and control techniques
- Create measures against undesirable emergent properties in AI

Regulatory:
- Create policies and safeguards against misaligned superintelligent AI
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