AI Ethics Needs Good Data
  In this chapter we argue that discourses on AI must transcend the language of
'ethics' and engage with power and political economy in order to constitute
'Good Data'. In particular, we must move beyond the depoliticised language of
'ethics' currently deployed (Wagner 2018) in determining whether AI is 'good'
given the limitations of ethics as a frame through which AI issues can be
viewed. In order to circumvent these limits, we use instead the language and
conceptualisation of 'Good Data', as a more expansive term to elucidate the
values, rights and interests at stake when it comes to AI's development and
deployment, as well as that of other digital technologies. Good Data
considerations move beyond recurring themes of data protection/privacy and the
FAT (fairness, transparency and accountability) movement to include explicit
political economy critiques of power. Instead of yet more ethics principles
(that tend to say the same or similar things anyway), we offer four 'pillars'
on which Good Data AI can be built: community, rights, usability and politics.
Overall we view AI's 'goodness' as an explicly political (economy) question of
power and one which is always related to the degree which AI is created and
used to increase the wellbeing of society and especially to increase the power
of the most marginalized and disenfranchised. We offer recommendations and
remedies towards implementing 'better' approaches towards AI. Our strategies
enable a different (but complementary) kind of evaluation of AI as part of the
broader socio-technical systems in which AI is built and deployed.
