Lightning round 3: Artificial intelligence and data
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Literature reviews are crucial in most research and writing processes. This session discusses a 'critically reflexive' user approach for students to compare and evaluate ‘traditional’ literature research tools with 'free', publicly accessible, generative artificial intelligence (GAI) tools. This task was part of a month-long student team project in "ENGR392: Social Impact of Technology". Students were asked to compare the outputs of at least 3 GAI tools, to that of ‘traditional’ manual compil...
Discover how switching between AI models mid-conversation can dramatically improve your results. Learn how different models have unique strengths in tone, intelligence, and specialization, and how to leverage these differences for better outcomes. Live demo to compare responses across models.
AI is insatiable. Shortly after generative AI gained popular attention, companies hawking their applications, online services, and various technologies rushed to plug AI into their products. Now, without even trying, many of us likely encounter and use AI in our own workflows but every time we do, AI uses more resources. And every picture you generate of a puppy making a pizza exacerbates greenhouse gas emissions. What can you do to diminish the impact of this technology? This lightning talk ...
This talk wants to share and discuss what skills still matter in data work, the risks AI introduces newcomers, and the challenges experienced professionals face when using AI to level up their data work.