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Ethical machines: data mining and fairness – the optimistic view Anna Ronkainen chief scientist, TrademarkNow it’s complicated, UU of Helsinki & Turku @ ronkaine 2016-05-02
My three points 1. people aren’t exactly perfect, either, and
sometimes algorithms can be an improvement
2. different types of algorithms needed for arriving at decisions and validating/disproving them
3. data protection law about automated decision-making needs to be taken seriously
Heuristics or biases?
(Dhami 2003)
Sometimes people fail in unexpected ways...
(Danziger et al (2011):Extraneous Factors in Judicial Decisions)
Systems 1 and 2 in legal reasoning: interaction System 1: making the decision System 2: validation and justification
(Ronkainen2011)
Implications for algorithms (hypothesis) - System-1-like processes cannot be captured
reliably with GOFAI -> machine learning and other statistical approaches needed
- the System 2 part (finding supporting arguments and validating/falsifying the decision candidate) can (and should) be implemented with rule-based GOFAI for accountability, maintainability etc etc etc
Taking data protection seriously?
(2016 EU General Data Protection Regulation)
Seriously-seriously?
(1995 EU Data Protection Directive 95/46/EC)
My three points 1. people aren’t exactly perfect, either, and
sometimes algorithms can be an improvement
2. different types of algorithms needed for arriving at decisions and validating/disproving them
3. data protection law about automated decision-making needs to be taken seriously
Thank you!