1. AI and jobs
A new EU Agenda
Andrea Renda

2. Three quotes
“The crisis takes a much longer time coming than you think, and then it happens much faster than you would have thought”
“A wealth of information creates a poverty of attention”
Dornbusch, "Expectations and exchange rate dynamics." The journal of political economy (1976): p. 1161
“At the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted”

3. Digital Technology as “enabler”
Competition
Collusion
Access
Discrimination
Digital Technology as “enabler”
Jobs
Unemployment
Enforcement
Infringement

4. Source: Winick (2018)

5. This time it’s different
Speed is different: humans won’t keep the pace of innovation:
Some jobs will be lost, ALL jobs will be affected
Trade and protectionism will be relied upon to mitigate some of these effects
Short term: major disruptions
Long term: we work less and differently, with better subjective well-being
Policy priorities
Work-train-life balance
Reforming education and skills
Redesigning the welfare system and the role and mission of trade unions
Redefining work?

6. The diffusion challenge: six growing divides
Between innovation-leading and lagging countries
Between cities and rural areas
Between leading firms and “zombie” firms
Between rich and poor
Between education “haves” and “have-nots”
Between “gifted” and “non-gifted”?

7. Data as labour? New forms of remuneration
Universal Basic Income incompatible with subjective well-being
“Heteromation” (Ekbia and Nardi 2017)
Communicative labour (social media, e.g. LinkedIN, Facebook)
Cognitive labour (e.g. upwork, mechanical turk)
Creative labour (modders)
Emotional labour (e.g. PARO)
Crowdsourced labour (citizen science)

8. Data as labour? Unlikely to work, at least for communicative labour
Scenario 1: all data are valued in the same way
Cross-subsididation, over-production of data
“Market for lemons”: social networks would be flooded with bad-quality data
Scenario 2: data are valued differently
Risk of escalating inequality, undermining social cohesion, and ultimately fragmenting the user base of existing digital platforms
Possible for other forms of work (cognitive, creative, emotional, crowdsourced)

9. Complementarity: Citizen/CEOs?
AI that helps us navigate the information-rich environment
Open source AI that “selects content for us”
AI solutions that enhance human capabilities

10. The EESC @60: future missions
Redefining work
Redefining welfare
Defining human-AI complementarity
Refocusing on SDGs and well-being
Shaping multi-level government strategies
Keeping track of co-regulatory schemes

11. AI and jobs
A new EU agenda
Andrea Renda