For the last 5 years, artificial intelligence and emerging technologies have come with lots of promises from business efficiency to digital services in international development and even peacemaking. The expansion of those technologies has also come with threats and challenges including ethical, political, social and legal concerns regarding diversity and inclusion.
As a manager or when working on an innovation project for sustainable development goals, you want to build a team that is diverse. You want to bring in the right talents with varied backgrounds both in terms of education and career journey. You also want to be able to identify gaps and find new talents. You want profiles that will motivate one another, create momentum and enrich the conversation around the table when brainstorming especially when envisioning the future or working on projects with a high impact on beneficiaries and citizens.
From a research I conducted on AI and its implications for women, it was no surprise that the systemic issue of equality and diversity in the workplace was cross-sectoral and of high importance when recruiting and when building HR systems. AI solutions are expected to account for indigenous people and vulnerable groups throughout the hiring/team-building cycle. Indeed, HR Tech systems powered with 4.0 tools are the most pragmatic, impactful and ‘easy’ to deploy solutions in midsized to large companies to improve their processes, while trying to shift their internal dynamic by onboarding outsiders or by moving current employees whose talent has not been tapped into across the corporation. To date, ‘some AI-recruitment tools developed for specific companies have already proven to have a ‘Lookalike audience’ feature [that] exclude audiences by ethnic or socio groups whether to reproduce a historic demographic in a working environment or to attract a certain demographic’ while some social platforms ‘use the ‘Ethnic Affinities’ feature (…) for advertisers to use demographic data to algorithmically target who will receive certain jobs and house ads’. (Martins de Nobrega, 2022). Another risk of losing talent is when the algorithm is trying to identify the perfect profiles by screening past recruitments crossed with results and years of experience within the company. Such an approach has been rapidly proven to duplicate the same profiling repeating the systemic bias and excluding certain groups, and therefore not enabling the company to attract new talents in line with the current needs of their market.
To deliver real impactful results to adapt the organisation to the challenge of world 5.0, it means that AI solutions should be designed with a human-centred approach and an algorithm that promotes and sustains the human factor.
The Human Factor remains the new goal and happily, for us, it does involve a diversity of experience, jobs and career paths. This agility is needed.
Because in the end, it is not just about building the right team. It is about giving everyone an equal opportunity whatever their journey and tapping into the unseen or unrepresented potential of every one of us.
Author: Virginie MARTINS de NOBREGA