How Toronto Declaration Affects AI Development
Purpose of Toronto Declaration
Artificial Intelligence is a double edge blade. Every opportunity has the potential to become a danger. Without the correct use and legislation, the artificial intelligence can easily be mismanaged and diluted by the people’s interest. For the concern, some experts disagree the free market approach and gave effort to the fact that to protect people from discriminatory algorithms a guideline is before nothing.
To reflect on the fact, human rights organizations like Human Rights Watch, Amnesty International, The Wikimedia Foundation, Access Now, and others asked the technological companies along with the government collaboration to adopt guiding principles to protect human rights. These organizations joined a pen to establish a declaration named as Toronto Declaration on Machine Learning.
The outcome of the Declaration
The declaration asks the engineers and developers to develop and revisit algorithms keeping the focus on the promotion of transparency and equality in the workstation and turn an end to algorithm propagated racism and discrimination.
It is a known fact the algorithms are so robust that based on the input data they can understand our implicit biases. Moreover, then they are being processed to give the potential list of people on to different activities, i.e., Police investigation, bank loan, target advertising. Thus, the online culture being shaped and so does the world as well.
The Toronto Declaration calls for a real solution in this matter. This document reflects from international human rights laws and states that if anyone being abused by the unscrupulous use of artificial intelligence algorithms must have a way to seek reparations.
As per the declarations:
Existing patterns of structural discrimination may be reproduced and aggravated in situations that are particular to these technologies – for example, machine learning system goals that create self-fulfilling markers of success and reinforce patterns of inequality, or issues arising from using non-representative or “biased” datasets.
All actors, public and private, must prevent and mitigate discrimination risks in the design, development and, application of machine learning technologies and that ensure that effective remedies are in place before deployment and throughout the lifecycle of these systems.
Unarguably the algorithms using by the big companies have a substantial discrimination effect to the large population. The Toronto Declaration is an effort to balance the discrimination effect. The rise of Artificial Intelligence and Machine learning increases the concerns, and a proper step must be taken to make sure the right use of it.
The Toronto Declaration is not legally binding, but it is essential to understand the need for it. There could be a couple of solution like include people in the development process from a different race, culture, gender, and socio-economic background, which will make sure there is a proper inclusion of each of the culture. Another could make machine learning system development more accountable by becoming more transparent so that it will be accountable more to any shortcomings.