Daniel Kaszyński (PhD) is an AI expert with more than ten years of experience working on analytical models and financial risk in corporate audit firms – the Big Four. Assistant at the Unit of Decision Analysis and Support at the SGH Institute of Econometrics and he is involved in the activities of AI Lab. His main area of specialization is operations research, mathematical optimization and forecasting models. He used to work for international banks with responsibility to construct, and validate analytical models. He has been twice the winner of the SGH student poll “Inspiration of the Year
implementation? Are we doomed to use AI tools while building up a narrative on the AI usage? (P)
Artificial Intelligence is transforming every aspect of our lives, from education to communication and working. To effectively introduce AI to the university, it is important to present not only its capabilities but also specific tools and ways of applying them in education, and research. AI offers a wide range of solutions, from advanced data processing algorithms to systems supporting text and image analysis.
However, when integrating AI into the academic environment, it is also essential to consider its limitations and risks such as ethical concerns, algorithmic bias, and fairness of AI systems.
In our presentation we will tackle these issues, while explaining what the concept of algorithmic bias means, and how it affects the operation of AI models. Discussion will be based on real-world cases to show how AI has demonstrated bias around such factors as gender, age, and ethnicity in recruitment system, judicial risk assessments, ad targeting, and healthcare.
Another critical question is whether we are doomed to use AI tools when discussing AI itself. Whereas AI facilitate research, writing, and analysis, it is not a must be. A thoughtful, human-led approach is worthwhile in shaping AI narratives and avoiding AI entirely may put individuals and institutions at a disadvantage.
Education plays a key role here. Thanks to AI literacy, people can take well-informed decisions, use AI tools effectively, and maximize benefits while ensuring fairness, transparency, and accountability.
Presentation with Ewelina Kędzior