The latest advancements in artificial intelligence (AI) and machine learning have brought to the forefront the crucial topic of Fairness-Aware Machine Learning and Generative AI for Social Good. This evolving field aims to develop algorithms and models that prioritize fairness, equity, and societal well-being.
Fairness-aware machine learning tackles the inadvertent biases and discrimination often found in AI systems, particularly in critical sectors like hiring, lending, criminal justice, and healthcare. By integrating fairness metrics and constraints into algorithm design and training, experts aim to mitigate discrepancies among different demographic groups and ensure fair outcomes.
On the other hand, Generative AI for social good harnesses the power of generative models such as generative adversarial networks (GANs) or variational autoencoders (VAEs) to address pressing societal issues. These models generate synthetic data mirroring real-world distributions, aiding in tasks like data augmentation, simulation, and overcoming data scarcity in domains like healthcare, climate science, and disaster response.
In a bid to delve into these ground breaking concepts, Islamic University of Technology Computer Society (IUTCS) hosted an insightful seminar titled "Fairness-aware Machine Learning (ML) and Generative AI for Social Good" featuring distinguished guest Professor Latifur Khan from The University of Texas at Dallas, USA. Attendees had the opportunity to explore the forefront of technology and cutting-edge applications of generative AI while engaging in discussions on the ethical dimensions of AI and its potential for societal benefit.
Overall, the convergence of fairness-aware machine learning and generative AI offers promising prospects for building AI systems that not only excel in performance but also actively contribute to fostering a more equitable and inclusive society.
The seminar took place on February 20th, 2024, inside IUT's DLT room at 2 pm, drawing attention to the significance of these advancements in shaping the future of AI for social good.