Big Picture
- The AI Entrepreneur’s Moral Dilemma: Should I Start a Company That Could Destroy Millions of Jobs? The article is of the ‘don’t get freaked out, job loss is overhyped’ variety.
- How Machines Destroy and Create Jobs. The historical perspective, nicely visualized.
HR’s View
- Microsoft Workplace Analytics Lifts the Veil on Employee Productivity. “Workplace Analytics taps into Office 365 email and calendar metadata, including to/from data, subject lines and timestamps, to shine a light on how the organization collaborates and spends time,” wrote Ryan Fuller, general manager of Workplace Analytics at Microsoft, in a July 5 blog post. “It turns this digital exhaust—the data that comes naturally from our everyday work—into a set of behavioral metrics that can be used to understand what’s going on in an organization.”
Execution
- So You’re Going To Manage a Data Science Team. Read this before you get started.
- Train a Neural Network to Play a Snake Game. Get a sense of what’s involved in a simple neural network.
Tutorial
- Artificial Intelligence Explained, Part 1. It’s never a mistake to refresh your definition. Scan this and forward it to your team and stakeholders.
- The ultimate, 3500-word, plain English guide to blockchain. Bookmark this reference.
- Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics. Bookmark and send around to your team. Great links, clear definitions.
Quote of the Week
“The first mistake organizations (and managers) make is thinking that the data scientists reporting to you are your whole team……
…..your actual team comprises stakeholders of various kinds — product owners, management, and (just as importantly) everyone else in technical roles, because what you do (and the insights you obtain) inevitably impacts the rest of the business and how it’s built/implemented/deployed/etc. You don’t exist in a vacuum, but rather are the conduit between what data you have (or, more often, don’t) and what the business needs to improve (and I’m deliberately avoiding the reverse flow here, which is when you’re asked by the business to improve something that’s already implemented).”
–So You’re Going To Manage a Data Science Team
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 seems to mean 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 8 to 10 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 Algorithmic HR.
