Business and the Atomic Human

Introduction: AI’s Impact on Business Information Flows

New Flow of Information

Evolved Relationship

Evolved Relationship

The Atomic Human

Networked Interactions

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.)

Information Topography: How AI Reshapes Organizational Decision Making

An Attention Economy

1. Human attention will always be a “scarce resource” (See Simon, 1971)
2. Humans will never stop being interested in other humans.
3. Organisations will keep trying to “capture” the attention economy.

Balancing Centralized Control with Devolved Authority

Question Mark Emails

Executive Sponsorship

• Direct sponsorship from the most senior executive.
  • This has a cultural effect as well as a direct effect.
• Bring about through involvement
  • develops understanding of capabilities of data science in exec team.

Pathfinder Projects

• In executive context: an important project that is interdepartmental.
• Should involve the CEO, CFO, CIO and data science team (or equivalents).

2016 US Elections

Techonomy 16

. . . the idea that fake news on Facebook . . . influenced the election in any way I think is a pretty crazy idea

Mark Zuckerberg Techonomy 16, 10th November 2016

Facebook estimates that as many as 126 million Americans on the social media platform came into contact with content manufactured and disseminated by the IRA

Facebook evidence, 30th October 2017

Human-Analogue Machines (HAMs) as Business Tools

Human Analogue Machine

HAM

Bandwidth vs Complexity

bits/min	\(100 \times 10^{-9}\)	\(2,000\)	\(600 \times 10^9\)

Understanding the Limitations

AlphaGo

Sedolian Void

Uber ATG

.

System Zero: The Risk of Data-Driven Manipulation

System Zero

Two Types of Stochastic Parrot

Superficial Automation

• AI enables automation of surface-level tasks
• Examples: Email writing, document summarization
• Risk of losing deeper value in the process

Hidden Value

• Email writing builds relationships
• Documentation creates institutional memory
  
• Human pauses enable reflection

The Automation Challenge

• Complex ≠ Complicated
• Speed isn’t always progress
• Augment humans, don’t replace them
  • See e.g. ai@cam public dialogues: https://ai.cam.ac.uk/projects/public-dialogues.html

Good Process Drives Purpose

Building Trust and Accountability in AI Systems

Institutional Character

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.

Practical Solutions for Business Implementation

Three AI Actions

• Data grooming: Do the basics right.
  • Incentivisation for data quality
• People training: At all levels
• Case studies

Attention Reinvestment Cycle

Intellectual Debt

Technical Debt

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

Separation of Concerns

Intellectual Debt

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

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

Dealing with Intellectual Debt

What we Did at Amazon

Are Right a Lot

Leaders are right a lot. They have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs.

Dive Deep

Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdote differ. No task is beneath them.

Thoughtsday

• Dealing with highly operational decision making.

What we did in DELVE

Delve Timeline

• First contact 3rd April
• First meeting 7th April
• First working group 16th April

Data at the Heart

• Use data to answer policy questions.
• Make international comparisons for input.
• Challenges: around getting data.

Data as a Convener

• Data allows externalisation of cognition.
• Even when not existing, can ask: What data would we want?

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

.

Conclusion: The Business Imperative

AI cannot replace atomic human

• AI reshapes information flows - understand your information topography
• Balance centralized control and devolved decision-making
• Recognize LLMs as interfaces, not substitutes for human judgment
• Build intelligent accountability into your AI deployments
• Focus on domain expertise leading AI implementation
• Invest in developing institutional character around AI use