The End Of Knowledge - Vault 1 - Lex 100 - 22 (2024) - Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI

graph LR classDef analogy fill:#f9d4d4, font-weight:bold, font-size:14px; classDef definition fill:#d4f9d4, font-weight:bold, font-size:14px; classDef challenges fill:#d4d4f9, font-weight:bold, font-size:14px; classDef potential fill:#f9f9d4, font-weight:bold, font-size:14px; classDef ethics fill:#f9d4f9, font-weight:bold, font-size:14px; classDef future fill:#d4f9f9, font-weight:bold, font-size:14px; linkStyle default stroke:white; Z[Melanie Mitchell:
Concepts, Analogies] -.-> A[Focus is on analogy's
role in human thought. 1,6,9,10] Z -.-> B[Prefers the term complex information
processing over AI. 2,3,4] Z -.-> E[Creating AI reflects a
desire for self-understanding. 5] Z -.-> G[Need dynamic cognitive models
beyond current machine learning. 7,8,11,12] Z -.-> M[AI has potential and
limits in creative domains. 13,15] Z -.-> P[AI developers have ethical
responsibilities to society. 16,17,18] A -.-> F[Analogy-making is fundamental
to human learning. 6] A -.-> I[Understanding and generating analogies
is an AI challenge. 9] A -.-> J[Copycat project attempted to computationally
model analogy-making. 10] B -.-> C[The definition of AI changes
as technology advances. 3] B -.-> D[AI excels in specific domains,
not general intelligence. 4] G -.-> H[Skeptical of deep learning achieving
human-level intelligence. 8] G -.-> K[Common sense is a
huge AI challenge. 11] G -.-> L["Commonsense knowledge problem"
is difficult to solve. 12] M -.-> N[Need realism about AI hype,
alongside its potential. 15] M -.-> O[Interdisciplinary research is
crucial to advance AI. 14] P -.-> Q[Mentors and curiosity are
important in AI careers. 17] P -.-> R[Future AI research must
overcome existing challenges. 18] class A,F,I,J analogy; class B,C,D definition; class G,H,K,L challenges; class M,N,O potential; class P,Q,R ethics; class E,Q,R future;

Custom ChatGPT resume of the OpenAI Whisper transcription:

1.- Melanie Mitchell's interest in AI focuses on the role of analogy in human thinking, influenced by work with Hofstadter and Holland.

2.- She finds the term "artificial intelligence" overly broad, preferring something like "complex information processing."

3.- The shifting perception of what counts as an AI achievement (e.g., chess) is discussed – as AI progresses, so does our definition of intelligence.

4.- Can AI surpass human intelligence? Mitchell stresses AI's domain-specific advances, not general intelligence.

5.- Why do we strive to create AI and artificial life? Mitchell connects this to a deep desire for self-understanding.

6.- Mitchell emphasizes the fundamental importance of analogy-making in human learning and concept development.

7.- Current machine learning approaches are powerful, but Mitchell sees the need for more dynamic, integrated cognitive models.

8.- She's skeptical that deep learning can achieve human-level intelligence without built-in concepts (using DeepMind's Atari success as a limited example).

9.- Could AI understand and generate analogies? This is a key challenge in mimicking human-like thought.

10.- The Copycat project aimed to computationally model analogy-making, illustrating this as a core human process.

11.- Common sense is a huge gap between current AI and human cognition.

12.- The "commonsense knowledge problem" highlights just how difficult it is to encode human-like understanding into machines.

13.- Mitchell and Fridman debate AI's future in creative domains, acknowledging its limits while seeing potential progress.

14.- Interdisciplinary research (computer science + cognitive science) is seen as crucial for advancing AI.

15.- Mitchell voices concerns about AI hype, advocating for realism about limitations alongside potential.

16.- The ethical responsibilities of AI developers in considering the societal impact of their work are discussed.

17.- Mitchell reflects on her career path, emphasizing the importance of mentors and deep curiosity in her AI journey.

18.- The interview concludes with a focus on the future of AI research, advocating for new approaches to overcome existing challenges.

Interview byLex Fridman| Custom GPT and Knowledge Vault built byDavid Vivancos 2024