Mind the Gap: Bridging Innovation’s Supply and Demand in the AI Era

AI Policy Challenges

• Public priorities: health, education, security, social care
• Current focus: creative content generation, commercial applications
• Result: innovation misalignment with societal needs

The Implementation Gap

• UK Horizon program: wrongful prosecutions of subpostmasters
• NHS Lorenzo project: cancelled with £10+ billion bill
• Root cause: gap between technology and human needs

From Philosopher’s Stone to AGI

• Philosopher’s stone: sought to transform base metals to gold
• Modern parallel: Artificial General Intelligence (AGI)
• Both concepts promise magical transformation

The AGI Misconception

• AGI based on flawed notion of rankable intelligence
• Like an “artificial general vehicle” for all journeys
• Intelligence is context-specific, not universal

Information Theory and AI

• Claude Shannon developed information theory at Bell Labs
• Information measured in bits, separated from context
• Makes information fungible and comparable

Information Transfer Rates

• Humans speaking: ~2,000 bits per minute
• Machines communicating: ~600 billion bits per minute
• Machines share information 300 million times faster than humans

Bandwidth vs Complexity

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

New Flow of Information

Evolved Relationship

Evolved Relationship

Revolution

The Risk of Digital Autocracy

• Ancient scribes controlled information through restricted literacy
• Modern digital oligarchy controls information through data asymmetries
• Information control creates power imbalances in society

Modern Information Asymmetries

• Algorithmic attention rents: excess returns from data control
• Human attention becomes the bottleneck in the system
• Power without corresponding social responsibility

• Machines automate human “mental labor” with algorithmic decisions
• Analogous to how machines previously automated physical labor
• Result: potential inflation of human capital

The New Productivity Paradox

• Original productivity paradox: investment without returns
• Required organizational restructuring to realize benefits
• Example: Amazon’s API mandate reorganized structure around software

From Quantity to Distribution

• Modern AI paradox: misalignment of innovation with societal needs
• Innovation concentrated in commercial, not social domains
• Gap between technological advancement and social value creation

The Innovation Flywheel

• Invests in R&D to produce technical innovations
• Innovations deployed as productivity improvements
• Improvements generate economic surplus
• Surplus reinvested in further R&D

The Attention Reinvestment Cycle

• Traditional innovation flywheel: R&D → Innovation → Productivity → Economic Surplus → R&D
• Problem: Misalignment with societal needs in healthcare, education, social care

A New Model for Innovation

• Attention Reinvestment Cycle liberates human attention
• Freed attention reinvested in knowledge networks
• Creates value through improved human services

Data Science Africa is a bottom up initiative for capacity building in data science, machine learning and AI on the African continent

Conclusion

• AI innovation must connect with societal needs
• Engage with piecemeal social engineers
• Move from grand narratives to practical deployment
• Bridge technical and social domains