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Blind Peer Review

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Ethical AI in Talent Assessment: Following True North in our Professional Calling

Presentation

In her book, The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI, ImageNet creator Fei-Fei Li continuously references the North Star as her moral signpost, guiding her on a human-centric, ethical trail as she traversed uncharted frontiers in the emergence of modern AI. Her work has been hailed as a source of inspiration and a call for continued scientific discovery to improve the human condition.

In this presentation, we focus on false stars that shimmer enticingly in the distance, tempting us with distractions and illusions, as well those steadfast constellations like Polaris (Fei-Fei Li’s North Star) that guide us with unwavering light towards developing and deploying ethical AI. In this regard, we will commence with establishing a mental image and conceptual framework of ethical AI in the context of talent assessment. This discussion will take as its centrepiece AI’s coming of age within the framework of the Assessment Centre (AC) method. Thereupon, we will investigate the manifestation and sources of biases, systemic inequalities, and practices that may harm or adversely affect AC participants. We will highlight risks and warning signs that, if not heeded, may lead to shortcuts, false insights, and ultimately compromise validity. This will be juxtaposed with guidelines for attaining fairness, transparency, and inclusivity, creating a fair and equitable talent assessment process that fosters genuine leadership potential.

The philosophical/theoretical component of this presentation will be grounded by practical insights and research findings gathered in developing AI solutions within the AC framework – particularly AI-administered and -scored video interview and simulation exercises.

We will conclude our session by proposing a taxonomy for evaluating AI-driven assessment methodologies against the Polaris or True North of ethical practice.

How will the delegates be able to apply your session content back on their job?

The assessment practitioner is increasingly faced with the proliferation of digital tools and AI-driven technologies that promise quick, scalable insights into human potential. However, Chamorro-Premuzic et al. (2016) warn that “shiny new talent identification objects” may “bamboozle” practitioners with little regard for the ethical responsibility we carry when making or shaping talent decisions.

This discussion will raise awareness of the risks and warning signs that could derail ethical AI in talent decision-making. It will also provide practitioners with an evaluative framework and guidelines for ensuring ethical best practices as we embrace new technologies in the AC space.

What type of tip/tool (e.g., a template, framework, etc.) will you leave the delegates with?

A conceptual framework for integrating theoretical perspectives and practice-based observations regarding ethical risks and best practices in the adoption of AI-driven technologies.

What do you want your audience to know at the end of your presentation and what will the three main points be?

o An understanding of ethical AI in the AC context.
o Awareness of risks and warning signs.
o Understanding of the requirements of ethical AI in talent assessment, with guidelines for achieving it in the AC space.

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