Decision Making in the Era of Generative AI

Henry Ford’s Faster Horse

Information and Embodiment

Claude Shannon

Embodiment Factors

New Flow of Information

Evolved Relationship

Evolved Relationship

Societal Effects

• This phenomenon has already revolutionised biology.
  • Large scale data acquisition and distribution.
  • Transcriptomics, genomics, epigenomics, ‘rich phenomics’.
• Great promise for personalized health.

Societal Effects

• Automated decision making within the computer based only on the data.
• Subjective biases need to be better understood.
• Particularly important where treatments are being prescribed.
  • Interventions could be far more subtle.

Societal Effects

• Shift in dynamic:
  • from direct human-data to indirect human-computer-data
  • modern data analysis is mediated by the machine
• This change of dynamics gives us the modern and emerging domain of data science

The Great AI Fallacy

There are three types of lies: lies, damned lies and statistics

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There are three types of lies: lies, damned lies and statistics

Benjamin Disraeli

There are three types of lies: lies, damned lies and statistics

Benjamin Disraeli 1804-1881

There are three types of lies: lies, damned lies and ‘big data’

Neil Lawrence 1972-?

Mathematical Statistics

‘Mathematical Data Science’

Human Communication

Heider and Simmel (1944)

In practice …

• There is a lot of evidence that probabilities aren’t interpretable.

• See e.g. Thompson (1989)

Number Theatre

Data Theatre

}{The focus so far has been on reducing uncertainty to a few representative values and sharing numbers with human beings. We forget that most people can be confused by basic probabilities for example the prosecutor’s fallacy.}{anne-llm-conversation}

In practice …

• LLMs are already being used for robot planning Huang et al. (2023)

• Ambiguities are reduced when the machine has had large scale access to human cultural understanding.

Inner Monologue

Behind the Eye

Later in the 1940's, when I was doing my Ph.D. work, there was much talk of the brain as a computer and of the early digital computers that were just making the headlines as "electronic brains." As an analogue computer man I felt strongly convinced that the brain, whatever it was, was not a digital computer. I didn't think it was an analogue computer either in the conventional sense.

Human Analogue Machine

Counterfeit People

• Perils of this include counterfeit people.
• Daniel Dennett has described the challenges these bring in an article in The Atlantic.

Psychological Representation of the Machine

• But if correctly done, the machine can be appropriately “psychologically represented”

• This might allow us to deal with the challenge of intellectual debt where we create machines we cannot explain.

The Accelerate Programme

• Research
• Teaching and learning
  • Ramp or Bridge model
• Engagement

Interface

AI for Science

One of biology’s biggest mysteries is how proteins fold to create exquisitely unique three-dimensional structures. Every living thing – from the smallest bacteria to plants, animals and humans – is defined and powered by the proteins that help it function at the molecular level.

So far, this mystery remained unsolved, and determining a single protein structure often required years of experimental effort. It’s tremendous to see the triumph of human curiosity, endeavour and intelligence in solving this problem. A better understanding of protein structures and the ability to predict them using a computer means a better understanding of life, evolution and, of course, human health and disease.

Professor Dame Janet Thornton, Director Emeritus of EMBL