Generative artificial intelligence: how do we mitigate the extreme risks?
Amidst the stark warnings of the risks of AI, we spoke with Assistant Professor Howard Zhong to explore effective solutions, such as AI regulation.
ChatGPT and generative artificial intelligence: What upheavals will the managers of the future face?
With the generative AI revolution, how can managers best approach this new technology that will change the way we work? Louis-David Benyayer this topic in his Executive Education white paper.
Harnessing AI to accelerate digital transformation
By overcoming challenges around data access and quality, access to talent and skills, as well as taking systematic approaches to AI, companies can ultimately unlock the potential for this technology to accelerate digital transformation.
Exploring the Future Beyond Large Language Models
Despite their undeniable success, LLMs are not without their problems and limitations. Gabriel Scali looks beyond LLMs to what is next for AI.
AI can replicate human creativity in two key ways – but falls apart when asked to produce something truly new
Is computational creativity possible? The recent hype around generative artificial intelligence (AI) tools such as ChatGPT, Midjourney, Dall-E and many others, raises new questions about whether creativity is a uniquely human skill.
Four non-tech conditions for AI to improve performance
Prof. Louis-David Benyayer derives four performance drivers from research about the factors influencing the success of artificial intelligence initiatives.
How to leverage AI tools like ChatGPT to do your job faster and better
Héctor González-Jiménez has some expert guidance on how to navigate the rise of generative AI tools — and avoid being supplanted by AI.
Even when algorithms outperform humans, humans can still make the difference
Prof. Louis-David Benyayer reflects on the strategic implications of research showing that under certain conditions, humans perform better than machines when it comes to decision-making.
3 steps businesses can take to reduce bias in AI systems
How can we ensure that AI development is fair, when the algorithms at its core are designed with biases? Profs. Lorena Blasco-Arcas and Hsin-Hsuan Meg Lee propose to a human-centred view for the design of specific frameworks and regulatory systems.
Algorithms in HR: for better or for worse?
Catherine Lespérance explains why the use of algorithms to determine whether an employee is efficient enough to stay on the payroll is controversial, and how to overcome the challenges of using algorithms in human resources to better modernise HR departments.
“To successfully integrate AI into strategic decision-making processes, you need a human-centred approach”
Understanding executives’ individual decision-making styles can help companies improve the use of AI in strategic initiatives and overcome flaws in human judgement, according to Christoph Keding and Philip Meissner.
Artificial intelligence in managerial decision-making
While AI does not yet match its cinematic representations, methodologies such as machine learning are turning it into a valuable tool for managers and businesses when it comes to decision-making and creating innovative solutions.
