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İçerik SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
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Learning to Unlearn with Melissa Sariffodeen

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Manage episode 419617775 series 3546664
İçerik SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Melissa Sariffodeen contends learning requires unlearning, ponders human-AI relationships, prioritizes outcomes over outputs, and values the disquiet of constructive critique.

Melissa artfully illustrates barriers to innovation through the eyes of a child learning to code and a seasoned driver learning to not drive. Drawing on decades of experience teaching technical skills, she identifies why AI creates new challenges for upskilling. Kimberly and Melissa then debate viewing AI systems through the lens of tools vs. relationships. An avowed lifelong learner, Melissa believes prior learnings are sometimes detrimental to innovation. Melissa therefore advocates for unlearning as a key step in unlocking growth. She also proposes a new model for organizational learning and development. A pragmatic tech optimist, Melissa acknowledges the messy middle and reaffirms the importance of diversity and critically questioning our beliefs and habits.

Melissa Sariffodeen is the founder of the The Digital Potential Lab, co-founder and CEO of Canada Learning Code and a Professor at the Ivey Business School at Western University where she focuses on the management of information and communication technologies.

A transcript of this episode is here.

  continue reading

58 bölüm

Artwork
iconPaylaş
 
Manage episode 419617775 series 3546664
İçerik SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.

Melissa Sariffodeen contends learning requires unlearning, ponders human-AI relationships, prioritizes outcomes over outputs, and values the disquiet of constructive critique.

Melissa artfully illustrates barriers to innovation through the eyes of a child learning to code and a seasoned driver learning to not drive. Drawing on decades of experience teaching technical skills, she identifies why AI creates new challenges for upskilling. Kimberly and Melissa then debate viewing AI systems through the lens of tools vs. relationships. An avowed lifelong learner, Melissa believes prior learnings are sometimes detrimental to innovation. Melissa therefore advocates for unlearning as a key step in unlocking growth. She also proposes a new model for organizational learning and development. A pragmatic tech optimist, Melissa acknowledges the messy middle and reaffirms the importance of diversity and critically questioning our beliefs and habits.

Melissa Sariffodeen is the founder of the The Digital Potential Lab, co-founder and CEO of Canada Learning Code and a Professor at the Ivey Business School at Western University where she focuses on the management of information and communication technologies.

A transcript of this episode is here.

  continue reading

58 bölüm

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