One big problem being that we have a tendency to trust the decision made by a computer. But we have to really aware of the biases in these systems. Part of this bias is part of the bigger problem endemic in the tech industry - that's it's overrepresented by white men who have a very limited world view and a particular set of biases. The system is often going to be made in the image of its creator.
1 Facial recognition
Recent studies by M.I.T. and the National Institute of Standards and Technology, or NIST, have found that while the technology works relatively well on white men, the results are less accurate for other demographics, in part because of a lack of diversity in the images used to develop the underlying databases.
2 Search engines
4 Cultural references
5 Elsewhere in the garden
Notes that link to this note (AKA backlinks).
An exhibition at the Barbican. Really good. Visually very powerful, also thought-provoking with regard to algorithmic bias.
Rather than contracting profiteering disaster capitalists to roll out technologies of dubious efficacy and inherent racial biases, it would be better to invest in reforms that build social safety nets and reduce structural inequality.
"FINALLY, WITHOUT BIAS"
- AI and ethics
- Intellectual property
- Digital regulation
- History of the textile industry
- Limbo: virtual experience of asylum
- Sustainable technology
- My Devices
- Smart cities
- Algorithmic bias and racism
- Online content moderation
- organisational tech policies
- predator prey modelling
- evolutionary and adaptive systems
- algorithmic decision-making
Technologies in this field, much like the humans that create them, invariably have biases and inaccuracies, and these biases and inaccuracies disproportionately impact historically marginalized groups.