The document discusses the complex economics of artificial intelligence. It argues that AI should be viewed not through simple economics but through a complex framework that considers organizational, market, social, and temporal dimensions of complexity. These dimensions generate uncertainty, information problems, externalities, path dependencies, and other issues that could lead AI development to diverge from desirable outcomes. A complex view of AI economics is needed to inform evidence-based policies that can shape trajectories of AI and avoid undesirable impacts.

1. nesta.org.uk @nesta_uk
The Complex Economics of Artificial
intelligence
Juan Mateos-Garcia [@JMateosGarcia]
Data for Policy Conference
London, 11th June 2019

2. Introduction Dimensions of complexity Implications
General Purpose Technologies
General Purpose Technologies transform the fabric of society

3. Introduction Dimensions of complexity Implications
General Purpose Technologies [II]
We should study its deployment with economics of complexity, not simplicity
Artificial Intelligence is a hyper-General Purpose Technology

4. Introduction Dimensions of complexity Implications
A definition
Sensor EffectorAnalyzerPrediction Decision
EnvironmentData Action
• Model design and training
• Data collection and processing
• Reward function and decision system design
• Supervision • Production system
Skills
ProcessesInfrastructure
Data
Functions
Capabilities
Inputs
AI system
Systems that respond flexibly to varied situations in order to inform or automate decisions: based on
machine (deep) learning
Fallible: Narrow, exploitable, unexplainable

5. Introduction Dimensions of complexity Implications
Ways to think about it
A powerful technology
A dangerous technology
Mass automation /
labour displacement
Discrimination and bias
Market power
Safety
SuperintelligenceManipulation and
exploitation
Economics of AI
AI is a technology that increases
productivity
It has economies of scale
Importance of complementary assets
Critical studies of AI
AI is a socially constructed
technology
It reproduces injustice
Importance of ethics, inclusion and
regulation
AI safety
AI is a potentially unsafe technology
It can be exploited and gamed, and it
can exploit and game
Importance of design, alignment and
control

6. Introduction Dimensions of complexity Implications
Towards a complex economics of AI
Simple economics of AI Complex economics of AI
Definition of technology An investment ($$)
A system, a trajectory and a set of
institutions
Drivers of development Expected benefits and costs History, culture and politics
Measure of impact
Increased productivity, income
share
Externalities, diversity and
flexibility, risk
Role of time
Lags due to the need to invest on
complementary investments
Sequences of events determine
outcomes, random events matter
Accepts the possibility of deployment
failures (like critical studies and safety
approaches)
Acknowledges the importance of
incentives and trade offs

7. Introduction Dimensions of complexity Implications
The overall picture
Organizational
Complexity
Market complexity Social complexity
Temporal
complexity
a b
c
The interaction of components at lower levels generate structures at higher levels, and those structure
shape behaviours at the lower levels
Arthur (2014), Nelson and Winter (1982), Simon (1968)

8. Introduction Dimensions of complexity Implications
Organisational complexity
Organizational
Complexity
Uncertainty about
adoption
Deviation from
desirable scenario
Uneven, disappointing
deployment
Undesirable
outcome
a b
c
Organisations need to adopt fallible technologies and adapt their processes
Integrating AI systems into complex organisational systems is easier for young
digital sectors, and this could create an AI divide.
Agrawal et al (2018) Bresnahan & Tratjenberg (1995)

9. Introduction Dimensions of complexity Implications
Market complexity
Market complexity
Information asymmetries
between actors
Deviation from
desirable scenario
Mediocre, unsafe and abusive
applications, internalization.
Undesirable
outcome
Information asymmetries are pervasive in the market
Visibility and malleability create ‘information
thickets’ in AI markets
Hadfield and Hadfield (2018), Lipton and Steinhardt (2018), Stilgoe et al (2013), Brundage et al (2018)

10. Introduction Dimensions of complexity Implications
Sociopolitical complexity
Social complexity
Dilemmas between groups
Deviation from
desirable scenario
Disruptive and unjust
deployment
Undesirable
outcome
AI deployment generates externalities ‘elsewhere in society’
Vulnerable groups are unfairly exposed to
algorithmic risks
Acemoglu & Restrepo (2019), Myers West et al (2019), Eubanks (2018)

11. Introduction Dimensions of complexity Implications
Temporal complexity
Temporal
complexity
Path dependency in time
Deviation from
desirable scenario
Irreversibilities and lock-in
to inferior trajectories
Undesirable
outcome
Technological, market and social trajectories are cumulative and path dependent
Some trajectories (deep learning?) get locked in because of their
short term advantages despite their long term risks
Marcus (2018), Arthur (1994), Dosi (1982)

12. Introduction Dimensions of complexity Implications
Policy
Intervention
principle
Evidence and
experimentation
Transparency and
compliance
Social solidarity
Preservation of
diversity
Directionality in
AI R&D&I
Organizational
Complexity
Market complexity Social complexity
Temporal
complexity
All the above create an active space for government intervention to shape AI trajectories of
deployment and diffusion, and avoid undesirable outcomes
These policies need to be informed by an evidence based developed through a new ‘Sciences (and
policies) of the Artificial’. I believe that a complex view of AI economics will be a critical component
of those new sciences.

13. nesta.org.uk @nesta_uk
juan.mateos-garcia@nesta.org.uk
@JMateosGarcia
Essay: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3294552
Summary blog: https://www.nesta.org.uk/blog/complex-economics-artificial-intelligence/