Fair Machine Learning combats biases

Thema:
Artifical intelligence

An AI tool bases its calculations on data. If the data is biased, the calculations will be biased. If there was once a male preference within a profession, then this will be adopted by AI tools for recruitment. So the AI tool may wrongly give a better judgement to men. This can be prevented by de-correlating the data from gender. Gender and possible related proxies will no longer be predictive for job suitability. TNO expects to use Fair Machine Learning to select appropriate candidates in a fair and unbiased manner.

TNO makes generative adversarial network models using fair machine learning

TNO carries out the de-correlation for Fair Machine Learning using a Generative Adversarial Network (GAN) model. This model tries to balance two conflicting criteria:

  1. Minimising the number of changes to the dataset
  2. Making sure that somebody’s gender is no longer identifiable from the remaining characteristics

When weighing up the criteria, the model generalises the existing characteristics of individuals into more general characteristics. An example would be generalising postcodes according to neighbourhoods, neighbourhoods according to cities and cities according to countries. The end result is a dataset in which a person’s gender (criterion 2) is practically unrecognisable. In short, the gender bias has disappeared from the dataset.

Fair machine learning is relevant to all forms of discrimination arising from historical data

Fair Machine Learning is relevant to all forms of discrimination and prejudice that arise from the use of biased data. In addition to recruitment and selection, it is also important that the AI algorithm is fair when it comes to supervision, inspection and enforcement tasks. Gender, religion and ethnicity should not be used as selection characteristics.

If used responsibly, AI machine learning tools can increase efficiency and effectiveness when finding comparable individuals for all kinds of selection tasks. However, historical biases (which are less striking without these AI tools) are being structurally and systematically furthered by them. Fair Machine Learning reduces and prevents such discrimination.

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Rob de Wijk on the rise of AI in geopolitical context

Informatietype:
Insight
27 September 2022

Anne Fleur van Veenstra, director of science at TNO’s SA&P unit, interviews Rob de Wijk, emeritus professor of international relations in Leiden and founder of The Hague Centre for Strategic Studies. Rob is also a much sought-after expert who appears on radio and television programmes. What does the rise of AI mean geopolitically and in armed conflicts?

Bram Schot on the impact of AI on mobility

Informatietype:
Insight
27 September 2022

Marieke Martens, science director at TNO and professor of automated vehicles at the Eindhoven University of Technology, talks to Bram Schot. Schot was the CEO of Audi until 2020, having previously held management positions at various car makers, including Mercedes and Volkswagen. Their conversation concerns the influence of AI on mobility. How will AI impact the production process? And what does a future with autonomous vehicles look like?

Eppo Bruins on AI in different government domains

Informatietype:
Insight
27 September 2022

Michiel van der Meulen, chief geologist for the Geological Survey of the Netherlands (GDN), speaks with Eppo Bruins. Bruins was educated as a nuclear physicist and has spent many years working in the world of science, innovation, and technology. Between 2015 and 2021, he was a Dutch member of parliament for the Christian Union. He was recently appointed chairman of the Advisory council for science, technology and innovation (AWTI). What will AI mean for the various government domains in the coming years?

Bas Haring on AI, science and philosophy

Informatietype:
Insight
27 September 2022

Michiel van der Meulen, chief geologist for the Geological Survey of the Netherlands (GDN), speaks with Bas Haring. Haring originally studied artificial intelligence, which at the time still fell under the umbrella of philosophy, which is why people started calling him a philosopher. He himself feels more like a ‘folk philosopher’: Haring tries to make science and philosophy accessible to a wider audience. In 2001, he published a children’s book about evolution, Cheese and the Theory of Evolution. What better springboard for a geologist and a philosopher to talk about AI?

Arnon Grunberg on AI, creativity and morality

Informatietype:
Insight
27 September 2022

Peter Werkhoven, chief scientific officer at TNO, talks to Arnon Grunberg from his base in New York. Grunberg made his breakthrough in 1994 with his novel, Blue Mondays. He has since become one of the Netherlands’ best-known authors. The two talked about AI over dinner some years ago. Today, they finally get the chance to continue their conversation. What is Grunberg’s view on creativity? Can it be taught to machines? And how do humans morally relate to machines?