This week, we focus on the changes and advances in the technology. In particular, the recent Uber crash is likely to slow down the evolution of autonomous cars. That should act as a warning to HR automators who want to make and inform decisions about human value, worth, opportunities, and supervision.
A broader look at the world suggests the potential for a very long economic downturn once the AI investment is made. The issue here is that demographic contractions and overinvestment will make the post-AI crash deep and sustained.
Tim Cook, Apple’s CEO is calling for deeper regulation of consumer data. It’s likely that the Facebook fiasco will convert into tighter governance. The results will spill into HR and have particular relevance for the places (employment branding, candidate experience) athat rely on personal data to operate.
The other articles include a suggestion that AI is way overhyped, IBM’s approach to using blockchain to protect privacy and Amazon’s release of ‘streaming algorithms.’
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
- Why the Automation Boom Could Be Followed by a Bust. Most forecasts about the impact of AI overlook two critical trends: the rise in inequality and the rapidly aging workforce. This HBR nugget describes the future of the economy in broad strokes…a decade-long period of growth followed by a severe contraction, all triggered by AI and automation. (via Azeem Azhar)
- It Certainly looks bad for Uber. Worth digesting. The limits of our machines’ capabilities are where the liability issues lie. The Uber crash story is instructive for HR automation scenarios because we are also dealing with the limits of human capabilities. It only takes a single widely-broadcast event to slow momentum to a crawl.
HR’s View
- Apple’s Tim Cook Calls for More Regulations on Data Privacy. Consumer regulations matter deeply to HR. The current trend to conflate consumer branding with employment branding (candidate experience) encourages the mining and utilization of individual data in patterns that resemble the comsumer approach. Expect to have to navigate deeper scrutiny. HR, Marketing and other public data consumers will have to align their approaches.
- Enhancing Individual Privacy with IBM Blockchain and Senzing ER. IBM recommends a tamper-resistant log (ie. Blockchain) as an integral part of a company’s privacy architecture.
- Labour-monitoring technologies raise efficiency—and hard questions: Pushing back against controlling bosses leaves workers more likely to be replaced by robots. “As Amazon and other firms embrace new tools to monitor and direct their workers, the difference between progress and dystopia comes down to whether workers feel comfortable demanding raises, and whether they can quit without fear of serious hardship. Indeed, firms could ponder such matters themselves before the inevitable backlash.”
Execution
- Don’t believe the hype about AI in business. Only 5% of companies have really integrated AI into their businesses. “To borrow a punch line from Duke professor Dan Ariely, artificial intelligence is like teenage sex: “Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.” Even though AI systems can now learn a game and beat champions within hours, they are hard to apply to business applications. (via David Perry)
Tutorial
- Amazon pulls back the curtain on SageMaker AI service. Machine Learning can consume ungodly amounts of storage and processing. This article describes ‘streaming algorithms’. A new service from Amazon called SageMaker acts like a governor on resource consumption while allowing the ML Training process to continue normally. Read this piece twice.
- Researchers Develop an AI System that Provides Textual and Visual Responses. We will be better off when the conversation between human and machine is conversational. This is a step in the right direction.
Quote of the Week
“Typically, in an investment boom of this kind, supply growth creates the demand for more supply—a virtuous cycle of growth. In the early 2020s, rapid investment in automation would likely offset a little more than half the negative impact of automation on employment, easing the demand constraint on growth and potentially mitigating the immediate displacement of millions of workers. But by the end of the 2020s, automation could eliminate 20% to 25% of current US jobs—40 million workers—hitting middle- to low-income workers the hardest. At the same time, many of the companies that invested heavily in automation will be saddled with assets that are out of step with demand.
That’s the crucial pivot between boom and bust. As the investment wave recedes, it risks leaving in its wake deeply unbalanced economies in which income is concentrated among those most likely to save and invest, not consume. Growth at that point would become deeply demand-constrained, exposing the full magnitude of labor market disruption temporarily hidden from view by the investment boom.
Consumers who have lost their jobs to automation will spend less, putting further downward pressure on demand. By the late 2020s, unemployment and wage pressures may exceed levels following the Great Recession in 2009. Income inequality, having grown steadily for a decade, could approach or exceed historical peaks, choking off economic growth.”
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.
