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The role of human intervention in fair and inclusive AI
For all the jobs that AI seeks to replace, a truly fair and inclusive AI ecosystem should entail recruitment of large groups of people from a diverse range of backgrounds, education levels, and disciplines.
With the exponential growth in development and uptake of AI decision-making tools, the race is on to develop trusted frameworks, governance, and regulation to ensure it remains fair, transparent and without entrenched bias.
Fairness in AI formed part of the key theme “Tech for Good” as part of this year’s Davos Agenda.
Within days of the Biden administration coming to power, the agenda to reverse the Trump world order began in earnest and included appointing diverse leaders in all manner of policy, science and technology fields. Addressing bias in technology is high on their agenda.
The stage has been set.
In the discourse for ways to achieve fair and unbiased AI, much is said about the need to ensure as a minimum that there is increased diversity amongst the developers and engineers responsible for creating artificial intelligence products. The ability for those working on AI tools from the ground up to be alive to, and eliminate biased datasets or criteria for algorithmic decision-making is imperative.
