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6 business risks of shortchanging AI ethics and governance

CIO Business Intelligence

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 145
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Big Data Joins The Fight Against Traumatic Brain Injuries

Smart Data Collective

The CDC reports that the incidents of admissions for these types of injuries rose around 54% between 2006 and 2014. Big data software is starting to reach neurosurgery departments in an effort to prevent brain injury complications during surgery and to better understand brain injuries.

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Data Privacy in the Digital Age: A Right or a Luxury?

Smart Data Collective

Hamburg data protection commissioner Johannes Caspar issued an emergency order prohibiting Facebook from processing this data for three months, citing a privacy policy update that violates European data protection laws. For instance, Facebook’s decision to buy WhatsApp in 2014 was based on data collected via the Onavo VPN.

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The Ethics of Data Exchange

Cloudera

Thanks to the Bermuda Principles agreement of 1996, a mechanism was in place for sharing human genome data within 24 hours of generation. As different researchers made discoveries about the virus and its effect on humans, they shared their data. Efforts are under way to break the natural tendency of corporations to hoard their data.

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Optimizing clinical trial site performance: A focus on three AI capabilities

IBM Big Data Hub

In an ideal scenario, they would be able to, with relative and consistent accuracy, predict performance of clinical trial sites that are at risk of not meeting their recruitment expectations. 2014 Bentley C, Cressman S, van der Hoek K, Arts K, Dancey J, Peacock S. Department of Health and Human Services.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Joint training, for example, adds an additional “explanation task” to the original problem and trains the system to solve the two “jointly” (see Bahdanau, 2014). For this demo we’ll use the freely available Statlog (German Credit Data) Data Set, which can be downloaded from Kaggle.

Modeling 139
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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

They can arise from data collection errors or other unlikely-to-repeat causes such as an outage somewhere on the Internet. If unaccounted for, these data points can have an adverse impact on forecast accuracy by disrupting seasonality, holiday, or trend estimation.