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On April 3, 2018, in HR Intelligencer, HRExaminer, by John Sumser
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Algorithms become policy.

Maybe that’s enough to say. When you purchase an AI product, you are buying a policy that is much harder to change than something in a policy manual. Algorithms become policy that is rigidly enforced.

This issue is darker than usual. It’s worth saying that our view of technology is fundamentally optimistic. But, you can’t realize the potential without a thorough examination of the pitfalls. Mostly, that means the problems associated with automating decision making in the workforce are complicated and resist easy fixes. In fact, easy fixes are the foundations of class action lawsuits. After all, what intelligent systems consume and produce is called evidence in a courtroom.

It will take you 45 minutes to consume the articles. It might take you all week to digest them.

John Sumser will be presenting on Wednesday, May 2, 2018 at the O’Reilly AI Conference in New York City taking place between April 30 – May 2, 2018.
 

Big Picture
  • Non-tech businesses are beginning to use artificial intelligence at scale. From the Economist. Includes passing references to a number of HRTech AI solutions.
  • The everyday ethical challenges of self-driving cars. The extreme cases, like ‘do I crash the car or run over the little old lady’ obscure the real ethical problems with AI. The mundane issues are irksome because they require a good deal of thought.”First, there is the fact that what is easy for humans is often hard for machines. Whether it is recognizing faces or riding bicycles, we are good at perception and mechanical tasks because evolution built these skills for us. That, however, makes these skills hard to teach or engineer. This is known as “Moravec’s Paradox.”Second, in a future where all cars are self-driving cars, small changes to driving behavior would make a big difference in the aggregate. Decisions made by engineers today, in other words, will determine not how one car drives but how all cars drive. Algorithms become policy.”
  • Satya Nadella email to employees: Embracing our future: Intelligent Cloud and Intelligent Edge. How Microsoft is pursuing AI at the core of the business.

 

HR’s View
  • Study reveals number of hours it takes to make a friend. If you are designing systems to promote engagement and inclusion, it’s important to understand how long it takes to become a member of the organization and what the hallmarks are. If the organization is built on friendships, make time for the relationships to bloom. Team building exercises that last a weekend are a slender start.
  • How Coders Are Fighting Bias in Facial Recognition Software. “Research released last month found that facial-analysis services offered by Microsoft and IBM were at least 95 percent accurate at recognizing the gender of lighter-skinned women, but erred at least 10 times more frequently when examining photos of dark-skinned women.” Here’s how they are tackling the problem. Note that the current method for minimizing bias involves accentuating it.
  • Commoditisation of AI, digital forgery and the end of trust: how we can fix it? It is becoming impossible to tell which information sources to trust. Further, it’s becoming impossible to tell fake from real. Advances in machine learning deliver bogus video that is indistinguishable from real. The question here is ‘how does HR ensure that organizational communications are legit?

 

Execution
  • The robots are killing Tesla. Cautionary note: “the world’s best carmakers, the Japanese, try to limit automation because it “is expensive and is statistically inversely correlated to quality.” Their approach is to get the process right first, then bring in the robots — the opposite of Musk’s.”
  • Algorithms Can’t Tell When They’re Broken and Neither Can We. In HR implementations, there must be a mechanism for monitoring algorithm performance and repairing it. So far, not so good.

 

Tutorial
  • What worries me about AI. “If most of our fears turn out to be irrational, inversely, most of the truly worrying developments that have happened in the past as a result of technological change stem from things that most people didn’t worry about until it was already there.” In the end, this long (worthwhile) read is suggesting that users need much more control over the AI in their lives.
  • AI in HR – how to understand what is happening. The predictably brilliant Andrew Marritt offers a solid guide to current AI in HR.

 

Quote of the Week

“… ethical quandaries are ubiquitous. Everyday, mundane situations are surprisingly messy and complex, often in subtle ways. For example: Should your city spend money on a diabetes prevention program or on more social workers? Should your local Department of Public Health hire another inspector for restaurant hygiene standards, or continue a program providing free needles and injection supplies?

These questions are extremely difficult to answer because of uncertainties about the consequences – such as who will be affected and to what degree. The solutions philosophers have proposed for extreme and desperate situations are of little help here.

The problem is similar with self-driving cars. Thinking through extreme situations and crash scenarios cannot help answer questions that arise in mundane situations.”

 

About

 
Curate means a variety of things: from the work of vicar entrusted with the care of souls to that of an exhibit designer responsible for clarity and meaning. At the core, it means something about the importance of empathy in organization. HRIntelligencer is an update on the comings and goings in the Human Resource experiment with Artificial Intelligence, Digital Employees, Algorithms, Machine Learning, Big Data and all of that stuff. We present a few critical links with some explanation. The goal is to give you a way to surf the rapidly evolving field without drowning in information. We offer a timeless curation of the intersection of HR and the machines that serve it. We curate the emergence of Machine Led Decision Making in HR. 
 

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