Ethical AI Community Building a Better Society From Barcelona to the World

On the 24th of November, we celebrated the first event organized by Citibeats in collaboration with NTT DATA and hosted by NTT DATA Living Lab to reunite some of the stakeholders of the tech sector to create together a more inclusive and representative society!

Ethical AI, Open Source, gender bias, responsible use of technology, and the impact on society are just some of the key topics of the event.

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Ethical AI Community Building a Better Society From Barcelona to the World

1

The Necessity of an Ethical AI Community

What do we refer to when we talk about "Ethical Al"? And why do we need an Ethical Al community? Abby Seneor, CTO at Citiboats, and Marcos Cuevas, CPO at Citibeats, explain, among other things, the reasons behind the initiative meant to change the Al paradigm and bring the debate. around ethics in Al to the next level; why ethical technology and responsible use of it is absolutely necessary to build a better society; and how the Ethical Al Community can become a seal of quality to assess the trustworthiness of technology.

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The Necessity of an Ethical AI Community

2

Handle with care - The responsible use of technology

Technology has the power to change the world and, if used in an ethical way, to positively impact society and citizens. But how to determine what is ethical and what is not? Where does the responsibility lie, on the creator of the technology or on the user, or maybe both? Abby Seneor, CTO at Citibeats, and David Pereira, Head of Data & Intelligence at NTT DATA, talk about how to use technology in a responsible way, to mitigate bias and inequalities and include everyone's voice in the decision-making process. Abby and David highlight concrete examples of how biased models can generate misinformation, and racist comments and contribute to the consolidation of biases.

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Handle with care - The responsible use of technology

3

Ethical AI for all - How ethical AI should drive the private sector

The private sector has constantly proved to have a key role in leading societal changes and improvements. Building ethical Al models and trustworthy algorithms should be a societal and commercial imperative for any company looking to establish a lasting and responsible bond with its clients.

Alex Combessie, Co-founder & CEO of Giskard, and Ryan Donnelly, Founder of Enz.ai talk, among other things, about the implications and benefits that the adoption of ethical Al would mean for private companies; how to avoid falling into "ethical washing; the necessity of better regulations and more transparent governance processes; and the importance of having an education system focused on training people to develop ethical tools and, on the other side, organizations designing actionable frameworks.

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Ethical AI for all - How ethical AI should drive the private sector

4

Gender bias and lack of representativity - A fairer technology for a fairer society

Irene Chausse, Head of Product at Citibeats, Cecilia MoSze Tham, Co-founder and Head of Strategy at allWomen, and Joana Barbany-Freixa, Consultant and expert adviser on Technology and ESG, discuss the necessary steps to minimize gender bias and increase representativity and inclusiveness in private and public companies.

To create solid bases of a democratic, equal society, according to our speakers, it is necessary to have a conjoined effort from the private and public sectors to align objectives, goals, and also incentives to promote truly inclusive policies. At the same time, it is fundamental to tackle the biases at all levels of the system and promote a deep change in the rules of the game and people's mentality.

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Gender bias and lack of representativity - A fairer technology for a fairer society

5

Jekyll Institute or Mrs. Hyde? Gender segmentation with Machine Learning

Arnault Gombert, Head of Data Science at Citibeats, presents the first contribution of Citibeats to the Ethical Al Community, an open algorithm to detect and reduce gender bias. Arnault also explains the results of Citibeats and Giskard collaboration, a batch of tests to assess the fairness of models.

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Jekyll Institute or Mrs. Hyde? Gender segmentation with Machine Learning

6

Openness and collaboration - How to improve and assess the quality of the models

Openness and collaboration, the two pillars of the Ethical Al Community, are fundamental to assessing and improving the quality of models. And better models also mean a more representative and inclusive society. Paula Serra, BI & Project Manager at Tech Barcelona, Nardino Osman, Researcher at IIIA-CSIC, and Arnault Gombert, Head of Data Science at Citibeats, analyze the potential positive impact on society that the integration of Citibeats' algorithm to detect gender bias would mean for private companies and public organizations. During the conversation, the speakers touch upon other topics such as the necessity of more transparency, explainability, and alignment of values in technology not just in Al; the need for a radical change, though within a very solid ethical and legal framework; the interaction and relationship between citizens and institutions; and the current state of ethical entrepreneurship.

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Openness and collaboration - How to improve and assess the quality of the models