AI Problems
What are the greatest risks and challenges to reliably charting a path to progress?
Problems and risks associated with AI.
Success
What does [successful integration with Artificial Intelligence look like?
You should really pause and reflect on the fact that many companies now are saying what we want to do is build AGI — AI that is as good as humans.
OK, what does it look like? What does a good society look like when we have humans and we have trillions of AI beings going around that are functionally much more capable? What's the vision like? How do we coexist in an ethical and morally respectable way?
And it's like… there's nothing. We're careening towards this vision that is just a void, essentially. And it's not like it's trivial either. I am a moral philosopher: I have no clue what that good society looks like.
Fulfilment
What does meaningful progress look like?
What does intelligence want to do?
- Why will AI care about humans? We don't care about ants.
- How can an ordinary person trust people in charge of alignment?
Failure
What does the path to failure look like? What signs and triggers need to be monitored and setup?
The biggest problem is a crisis of trust, technological innovation driven by the advertising dollar has eroded people's trust in public institutions, in many cases for very good reasons.
Are we giving away the agency to manifest our own destiny?
No Voice No Choice
Everyday people have no idea, no voice or choice.
- Improving AI literacy: Developing accessible educational resources to help people understand key AI concepts and implications.
- Promoting diverse voices: Ensuring a range of perspectives from different fields and backgrounds are represented in AI discussions.
- Encouraging critical thinking: Teaching people how to evaluate sources, recognize biases, and think critically about AI claims.
- Fostering public dialogue: Creating forums for open discussion and debate on AI issues at local and community levels.
- Transparent reporting: Pushing for clear, jargon-free communication from AI companies and researchers about their work and its potential impacts.
- Independent oversight: Supporting the development of trusted, independent bodies to monitor AI progress and provide balanced assessments.
- Emphasizing shared values: Framing AI discussions around common human values and concerns to make the issues more relatable.
Challenges
The future with AI is likely to be far more complex and potentially disruptive than that utopian vision given these challenges:
- Accelerated development: AI progress is outpacing many predictions, with capabilities advancing rapidly in areas like language understanding, problem-solving, and even creativity.
- Job displacement: While AI will create new jobs, it's likely to eliminate or significantly alter many existing roles across various sectors, potentially leading to widespread economic disruption.
- Ethical concerns: As AI becomes more advanced, we'll face increasingly complex ethical dilemmas related to privacy, decision-making, and the potential for AI to be used in harmful ways.
- Power concentration: The development of powerful AI systems could lead to further concentration of wealth and influence among a small number of tech companies or nations.
- Existential risks: As AI capabilities approach or surpass human-level intelligence, there are legitimate concerns about potential loss of control and existential risks to humanity.
- Social and psychological impacts: Widespread AI integration could fundamentally change human interactions, relationships, and even our concept of work and purpose.
- Governance challenges: Regulating and controlling AI development on a global scale presents unprecedented challenges for policymakers and international cooperation.
- Unpredictable breakthroughs: The non-linear nature of AI progress means we could see unexpected leaps in capabilities that rapidly transform multiple aspects of society.