14–17 Oct 2019

Schedule: Impact of AI on Business and Society sessions

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13:4514:25 Wednesday, 16 October 2019
Location: Windsor Suite
Average rating: *****
(5.00, 3 ratings)
In the rapidly changing world of AI, adopting the right design principles is key. From data scientists and business users to client end users, IBM Watson always seeks to augment their capabilities. Ariadna Font Llitjós examines how IBM Watson applies ethical AI and user-centered design principles from the beginning and leverages them throughout the product development cycle. Read more.
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16:5017:30 Wednesday, 16 October 2019
Location: Windsor Suite
Charlotte Han (Independent)
Average rating: *****
(5.00, 1 rating)
According to research by AI2, China is poised to overtake the US in the most-cited 1% of AI research papers by 2025. The view that China is a copycat but not an innovator may no longer be true. Charlotte Han explores what the implications of China's government funding, culture, and access to massive data pools mean to AI development and how the world could benefit from such advancement. Read more.
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11:5512:35 Thursday, 17 October 2019
Location: King's Suite - Balmoral
Ganes Kesari (Gramener), Soumya Ranjan (Gramener)
Average rating: *****
(5.00, 1 rating)
In many countries, policy decisions are disconnected from data, and very few avenues exist to understand deeper demographic and socioeconomic insights. Ganes Kesari and Soumya Ranjan explain how satellite imagery can be a powerful aid when viewed through the lens of deep learning. When combined with conventional data, it can help answer important questions and show inconsistencies in survey data. Read more.
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16:0016:40 Thursday, 17 October 2019
Location: King's Suite - Balmoral
Weifeng Zhong (Mercatus Center at George Mason University)
Average rating: ****.
(4.00, 1 rating)
Weifeng Zhong explores a novel method to learn structural changes embedded in unstructured texts based on the Policy Change Index (PCI) framework developed by economists Julian Chan and Weifeng Zhong. He explains how an off-the-shelf application of deep learning—with an important twist—can help you detect structural break points in time series text data. Read more.
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16:5017:30 Thursday, 17 October 2019
Location: Windsor Suite
Secondary topics:  Text, Language, and Speech
Voiced-based AI continues to gain popularity among customers, businesses, and brands, but it’s important to understand that, while it presents a slew of new data at our disposal, the technology is still in its infancy. Andreas Kaltenbrunner examines three ways voice assistants will make big data analytics more complex and the various steps you can take to manage this in your company. Read more.

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