Algorithmic Trade-offs Between Accuracy and Fairness in Responsible AI, in conversation with Dr. Shaina Raza

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Mutual Connections with Shayan Mashatian

Shayan Mashatian

9 episodes

6 months ago

Mutual Connections is a podcast dedicated to exploring the ways people across industries are using technology and AI to create meaningful change. Hosted by Shayan Mashatian, a seasoned entrepreneur and AI expert, the podcast delves into stories of innovation, resilience, and purpose with a focus on Trustworthy and Responsible AI.

Each episode brings in remarkable individuals—from tech visionaries to healthcare disruptors—who share their experiences, challenges, and insights on leveraging AI and technology to solve some of the world’s most complex problems. Together, Shayan and Akifa guide listeners through conversations that reveal the power of shared connections and shared goals, uncovering not only the "how" but the "why" behind impactful innovation.

Join us to be inspired, learn from thought leaders, and discover the web of Mutual Connections shaping our future.

About host:

Shayan Mashatian is a serial entrepreneur with a passion for leveraging technology and design for social innovation. His career began in the early days of the Internet, where he was instrumental in building the first ISPs and Internet nodes. Over the past two decades, he has navigated various information technology waves, including web applications, mobile apps, platforms, and AI. Shayan has founded six startups, three in AI, and has delivered over 50 projects and products in several countries, working across diverse cultures from the Middle East to Canada, the US, Africa, and Asia. In recent years, Shayan has focused on AI and machine learning to personalize experiences in various industries, including security, privacy, health, and education. He is researching and publishing about Trustworthy AI, especially in the domain of healthcare. Shayan excels at assembling high-performing teams to solve wicked problems. As his LinkedIn title suggests, he is a Chief Glue Officer who orchestrates brilliance by connecting witted minds.

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Join us to be inspired, learn from thought leaders, and discover the web of Mutual Connections shaping our future.

About host:

Hosted on Acast. See acast.com/privacy for more information.

Algorithmic Trade-offs Between Accuracy and Fairness in Responsible AI, in conversation with Dr. Shaina Raza

Mutual Connections with Shayan Mashatian

1 hour 19 minutes 34 seconds

9 months ago

Algorithmic Trade-offs Between Accuracy and Fairness in Responsible AI, in conversation with Dr. Shaina Raza

Welcome to another insightful episode of Mutual Connections! I'm your host, Shayan Mashatian, and today we’re diving deep into the world of responsible AI with a distinguished expert, Dr. Shaina Raza. As an applied machine learning scientist at the Vector Institute for Artificial Intelligence, Dr. Raza is a leading voice in AI fairness, bias mitigation, and sustainable AI practices. In this conversation, we explore the ethical considerations of AI, the balance between accuracy and fairness, and the evolving landscape of generative AI. Whether you’re an AI enthusiast, researcher, or simply curious about the future of technology, this episode offers invaluable insights into one of the most critical discussions in the field today.

Highlights of the Conversation:

The Journey to Fairness in AI – The transition from optimizing news recommender systems to realizing the impact of filter bubbles and bias in AI models.
The Accuracy vs. Fairness Trade-off – The challenge of balancing high accuracy with fairness and diversity in AI models.
Bias in AI: Sources and Impact – How bias can arise from data imbalances, algorithmic design, or societal structures, and why it is critical to address it.
Techniques for Bias Mitigation – Various strategies such as adjusting data representation, applying fairness constraints, and fine-tuning algorithms.
The Role of Synthetic Data – Exploring the benefits and risks of using synthetic data to address bias due to a lack of diverse real-world data.
Evaluating Fairness in AI Models – Quantifying fairness using demographic breakdowns and statistical measures to ensure balanced outcomes.
The DeepSeek Effect and Open-Source AI – The rise of open-source AI models, their accessibility, and how they compare to proprietary models in terms of fairness and ethical implementation.
Sustainable AI and Carbon Footprint Considerations – The environmental impact of large AI models and efforts to develop more efficient, lower-emission alternatives.
Adversarial AI and Red Teaming – Using adversarial training techniques to detect misinformation, deepfakes, and unintended biases in AI models.
Future of AI: Where Are We Headed? – The shift from large, general-purpose models to smaller, specialized models tailored for industry-specific applications, and the growing importance of application layers over foundational AI models.

AI development should not be driven by hype but by a commitment to responsible, fair, and ethical practices. As AI continues to evolve, researchers, practitioners, and organizations must prioritize fairness and accountability in its implementation.

Tune in to this thought-provoking episode and join the conversation on the future of AI fairness and responsibility!

Hosted on Acast. See acast.com/privacy for more information.

Mutual Connections with Shayan Mashatian

Join us to be inspired, learn from thought leaders, and discover the web of Mutual Connections shaping our future.

About host:

Hosted on Acast. See acast.com/privacy for more information.