AI for Investors

What machine intelligence is, and where judgment still decides value

Neil D. Lawrence

The Cadogan Hotel, 75 Sloane Street, London SW1X 9SG

Part 1: What AI Is and Isn’t

Information and Embodiment

Claude Shannon

Embodiment Factors

bits/min billions 2,000
billion
calculations/s 		~100 a billion
embodiment 20 minutes 5 billion years

Communication Bandwidth

  • Human communication: walking pace (2000 bits/minute)
  • Machine communication: light speed (billions of bits/second)
  • Our sharing walks, machine sharing …

Part 2: How AI Changes the Firm

  • Human intelligence is locked-in
  • This makes it a bottleneck

What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention …

Simon (1971)

Intellectual Debt

Technical Debt

  • Compare with technical debt.
  • Highlighted by Sculley et al. (2015).

Lean Startup Methodology

The Mythical Man-month

Separation of Concerns

  • Decompose your complex problem/task into parts.
  • Each part manageable (e.g. by a small team)
  • Recompose to solve total problem

Addresses Complex Challenge

  • Highly successful approach to complex tasks.
  • Tuned to the human bandwidth limitation.
  • But the whole system still hard to understand.

Intellectual Debt

  • Technical debt is the inability to maintain your complex software system.
  • Intellectual debt is the inability to explain your software system.

Institutional Character

Bezos memo to Amazon in 2002

The API Mandate

  • All teams will henceforth expose their data and functionality through service interfaces.
  • Teams must communicate with each other through these interfaces.

  • There will be no other form of inter-process communication allowed: no direct linking, no direct reads of another team’s data store, no shared-memory model, no back-doors whatsoever. The only communication allowed is via service interface calls over the network.

  • It doesn’t matter what technology they use.
  • All service interfaces, without exception, must be designed from the ground up to be externalizable. That is to say, the team must plan and design to be able to expose the interface to developers in the outside world. No exceptions.

Duality of Corporation and Information

  • What is less written about is corporate structure.
  • This information infrastructure is reflected in the corporation.
  • Two pizza teams with devolved autonomy.
  • Bound together through corporate culture.

Conway’s Law

Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication structure.

Conway (n.d.)

Amazon and Agility

  • Company prides itself on agility.
  • Operates through a system of devolved autonomy
    • Teams have defined inputs and outputs.
  • Corporate culture bonds them togethether.
    • Customer obsession
    • Ownership

Cambridge

  • Over 800 years old.
    • Less commonly thought of as agile.
    • Reliable institutional character.
    • Amazon in comparison is more mecurial.

Organisational Data Science

  • Claim:
    • For data driven decision making to work there must be an interplay between institutional character and the information infrastructure.

Cultural Transplant

  • Claim:
    • Transplanting another organisation’s decision making infrastructure directly leads cultural rejection from the new host.

Part 3: Investor Implications

Productivity Flywheel

Supply Chain of Ideas

  • Ideas flow from creation to application like physical supply chains
  • Parallels with traditional economic supply chain management
  • Particularly relevant for IT and AI solutions

Supply Chain of Ideas

  • Current imbalance between supply and demand sides
    • Mismatch between macroeconomic interventions and microeconomic need
  • Over-Focus on solutionism
    • technologies/companies
  • Under-focus on real-world needs … disconnect between government and citizens … disconnect between companies and customers

Supply Chain of Ideas

  • Need to map idea problems demand to idea supply
  • Need to understand … problems (demand) … current “stock” of solutions (supply)
  • Requires active management of idea resources
  • Shape supply to meet demand

Common Investor Questions

Key Investment Questions

  • Market size vs hype
  • Sector timing differences
  • Competitive dynamics
  • Defensive characteristics

Risk Considerations

  • Technical limitations
  • Regulatory environment
  • Market dynamics
  • Valuation methods

Thanks!

References

Brooks, F., n.d. The mythical man-month. Addison-Wesley.
Conway, M.E., n.d. How do committees invent? Datamation 14, 28–31.
Lawrence, N.D., 2024. The atomic human: Understanding ourselves in the age of AI. Allen Lane.
Sculley, D., Holt, G., Golovin, D., Davydov, E., Phillips, T., Ebner, D., Chaudhary, V., Young, M., Crespo, J.-F., Dennison, D., 2015. Hidden technical debt in machine learning systems, in: Cortes, C., Lawrence, N.D., Lee, D.D., Sugiyama, M., Garnett, R. (Eds.), Advances in Neural Information Processing Systems 28. Curran Associates, Inc., pp. 2503–2511.
Simon, H.A., 1971. Designing organizations for an information-rich world. Johns Hopkins University Press, Baltimore, MD.