How quickly is AI advancing? And should you be working in the field? (with Danny Hernandez)

Aug 23, 2023 1h 8m 10 insights Episode Page ↗
Spencer Greenberg and Danny Hernandez discuss the future of AI, highlighting its predictable exponential progress driven by hardware, spending, and algorithmic improvements. They explore AI's profound implications for labor, job displacement, and the concentration of power, urging individuals to consider careers in AI safety for deep meaning and impact.
Actionable Insights

1. Pursue Meaningful AI Safety Work

Consider a career in AI safety (e.g., alignment, interpretability, policy, security) for deep personal meaning and high impact, as it’s presented as the highest expected value work, even if it involves a modest pay cut or perceived demotion. Competent engineers and security professionals can contribute without prior AI expertise.

2. Bet on AI Career Growth

Consider making a significant career move into AI, as its underlying exponential progress trends in hardware, spending, and algorithms are expected to continue for 10-20 years, offering a safe bet for long-term growth and impact.

3. Anticipate Job Automation & Reskill

Avoid training for jobs highly susceptible to AI automation (e.g., radiology, certain legal/medical tasks involving recall or well-defined data analysis) and proactively prepare to reskill, as AI systems are expected to increasingly replace or amplify human labor.

4. Simplify Difficult Decisions

Focus on 1-3 top considerations when making difficult decisions, rather than a long list of pros and cons, because the importance of concerns isn’t normally distributed. Consolidate smaller concerns into higher-level abstractions (e.g., overall well-being, impact) to clarify the most relevant factors and simplify the choice.

5. Scrutinize Happiness Assumptions

Critically examine your assumptions about what brings happiness by reflecting on past experiences of sustained joy, rather than relying on societal narratives. This helps to better understand your personal path to a good life and avoid unscrutinized beliefs.

6. Explore Diverse AI Safety Roles

Investigate specific areas within AI safety like alignment (ensuring models share human values), alignment science (measuring safety), mechanistic interpretability (understanding AI internals), AI policy, or lab security, as these offer various ways to contribute to making AI beneficial.

7. Assess Job Automation Risk

Evaluate job roles based on their amenability to AI: tasks with high economic value, clear definitions, and abundant training data are at higher risk of automation, while those requiring physical interaction or emotional intelligence (e.g., nursing) are currently safer.

8. Develop AI Management Skills

Focus on developing skills in managing AI systems, such as prompt engineering or building AI systems, as these will be crucial for leveraging AI capabilities and influencing the world in the future workforce.

9. Take Ownership in Friendships

Actively pursue potential friendships by getting contact information, initiating follow-up invitations (one-on-one or events), and being prepared for potential rejection. This proactive approach can accelerate friendship formation compared to passively waiting for unplanned interactions.

10. Enhance Meditation with AI Models

Apply AI-inspired mental models to meditation: recognize that retreats improve signal-to-noise ratio by removing external distractions, and understand that reducing preferences or goal orientation can lead to a state of perceived perfection.