The world has always been a lopsided, unfair mess--a statement that holds true regardless of whatever business sector you talk about or whichever country you visit. The rich, despite constituting less than 5% of the global population, always seem to wield an unfair influence over the rest--in a relative sense, the have-nots. Giant corporations trample over local businesses when they set up shop in a new country. Issues such as racism, sexism and unfair economic divide have been prevalent for what feels like an eternity. Technologies such as AI, computer vision and NLP were supposed to bridge this gap.

In this paper, we formulate the problem of selecting a set of individuals from a candidate population as a utility maximisation problem. From the decision maker's perspective, it is equivalent to finding a selection policy that maximises expected utility. Our framework leads to the notion of expected marginal contribution (EMC) of an individual with respect to a selection policy as a measure of deviation from meritocracy. In order to solve the maximisation problem, we propose to use a policy gradient algorithm. For certain policy structures, the policy gradients are proportional to EMCs of individuals. Consequently, the policy gradient algorithm leads to a locally optimal solution that has zero EMC, and satisfies meritocracy. For uniform policies, EMC reduces to the Shapley value. EMC also generalises the fair selection properties of Shapley value for general selection policies. We experimentally analyse the effect of different policy structures in a simulated college admission setting and compare with ranking and greedy algorithms. Our results verify that separable linear policies achieve high utility while minimising EMCs. We also show that we can design utility functions that successfully promote notions of group fairness, such as diversity.

When making a start in a new field it is common to feel overwhelmed. You may lack confidence or feel as though you are not good enough or that you are lacking some prerequisite. You will explore these issues in this post and learn that such feelings can lead to actions that can consume a lot of time and resources and leave you feeling disappointed in yourself. You will learn that there are many paths through the field of machine learning and that like programming, it is a meritocracy. Feeling like you are not good enough or that you are lacking some skill that you think you must have before you can make a start in machine learning is dangerous thinking.

On paper alone you would never guess that I grew up poor and hungry. My most recent annual salary was over $700,000. I am a Truman National Security Fellow and a term member at the Council on Foreign Relations. My publisher has just released my latest book series on quantitative finance in worldwide distribution. None of it feels like enough. I feel as though I am wired for a permanent state of fight or flight, waiting for the other shoe to drop, or the metaphorical week when I don't eat. I've chosen not to have children, partly because--despite any success--I still don't feel I have a safety net. I have a huge minimum checking account balance in mind before I would ever consider having children. If you knew me personally, you might get glimpses of stress, self-doubt, anxiety, and depression.

WASHINGTON, DC – Around 1200 BC, the Shang Dynasty in China developed a factory system to build thousands of huge bronze vessels for use in everyday life and ritual ceremonies. In this early example of mass production, the process of bronze casting required intricate planning and the coordination of large groups of workers, each performing a separate task in precisely the right order. A similarly complex process went into fashioning the famous army of terracotta warriors that Qin Shi Huang, China's first emperor, unveiled one thousand years later. According to the Asian Art Museum in San Francisco, the statues "were created using an assembly production system that paved the way for advances in mass production and commerce." Some scholars have speculated that these early forms of prescriptive-work technologies played a large role in shaping Chinese society.

A meritocracy is all about rewarding people on the basis of their abilities. This almost always turns out to be those people who work harder and take bigger risks. It's what has made our present day society so great. Everything you see around you today is the result of a meritocracy that rewards those people who work the hardest and accomplish the most. The social media platforms people use to spew forth outrage about the "myth of meritocracy" and how "unfair the system is" fail to realize that it's a meritocracy that has motivated the founders of said platforms to forgo evenings in front of the television in favor of 70-hour work weeks to build something that made them quite wealthy.

A meritocracy is all about rewarding people on the basis of their abilities. This almost always turns out to be those people who work harder and take bigger risks. It's what has made our present day society so great. Everything you see around you today is the result of a meritocracy that rewards those people who work the hardest and accomplish the most. The social media platforms people use to spew forth outrage about the "myth of meritocracy" and how "unfair the system is" fail to realize that it's a meritocracy that has motivated the founders of said platforms to forgo evenings in front of the television in favor of 70-hour work weeks to build something that made them quite wealthy.

On paper alone you would never guess that I grew up poor and hungry. My most recent annual salary was over $700,000. I am a Truman National Security Fellow and a term member at the Council on Foreign Relations. My publisher has just released my latest book series on quantitative finance in worldwide distribution. None of it feels like enough though. I feel as though I am wired for a permanent state of flight or fight, waiting for the other shoe to drop, or the metaphorical week when I don't eat. I've chosen not to have children, partly because--despite any success--I still don't feel I have a safety net. I have a huge minimum checking account balance in mind before I would ever consider having children. If you knew me personally, you might get glimpses of stress, self-doubt, anxiety, and depression.

Last month, at the world's leading general management conference--the Drucker Forum in Vienna Austria--Julian Birkinshaw, Professor of Strategy and Entrepreneurship at the London Business School and Director of the Deloitte Institute of Innovation and Entrepreneurship, declared provocatively that we are living in "the Age of Agile." The full text of Julian's important talk is set out below. He also has a new book coming out next year entitled Fast/Forward: Make Your Company Fit For the Future. Earlier this week, I discussed these issues with Julian. Steve Denning: In your talk, you spoke about three possible forms of organization: bureaucracy, meritocracy and adhocracy. Could you tell us more? Julian Birkinshaw: Bureaucracy is about and occupying roles and following rules. Meritocracy is a knowledge-based view of the organization, including big data and analytics. Adhocracy is an action-based view of the organization focused on capturing opportunities, solving problems and getting results. Denning: Where does "the age of Agile" fit into this scheme?

The video game arcade is the cathedral of the games industry. Veteran players see these increasingly endangered places as shrines to design purity, difficulty and player skill, bathed in the glow of flickering monitors. They were, after all, the places where the conventions of the medium were forged, and their gradual disappearance has only served to make them more alluring. Mobile gaming, meanwhile, receives a great deal less reverence, thanks in part to its vast popularity. Despite design masterpieces like Monument Valley, The Room and Hearthstone, smartphone titles are collectively seen as casual time-killers, lacking cultural clout.