Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs.
The UK has a new AI centre – so when robots kill, we know who to blame The UK has a new AI centre – so when robots kill, we know who to blameArtificial Intelligence 12 Oct 2016.
But while AI and machine learning are very much related, they are not quite the same thing. AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as “the science of getting computers to act without being explicitly programmed”. You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.
The digital revolution, we are told everywhere today, produces democracy. It gives “power to the people” and dethrones authoritarians; it levels the playing field for distribution of information critical to political engagement; it destabilizes hierarchies, decentralizes what had been centralized, democratizes what was the domain of elites.
Most on the left would endorse these ends. The widespread availability of tools whose uses are harmonious with leftist goals would, one might think, accompany broad advancement of those goals in some form. Yet the left today is scattered, nearly toothless in most advanced democracies. If digital communication technology promotes leftist values, why has its spread coincided with such a stark decline in the Left’s political fortunes?
New York is an iconic city with a rich history of innovation. I have a lot of family in New York and grew up visiting the city. Now that I’m living in Seattle, thousands of miles away, I don’t get to visit very often. However, I thought it might be fun to see if I could explore New York from the comfort of my desk using Excel. Through a little Internet searching, I discovered New York City’s “PLUTO” dataset. Created by the Department of City Planning, the PLUTO dataset includes information on every building in the city—more than 500,000 in total. I downloaded the dataset as CSV files and using Power Query for Excel, imported the data directly into Excel. I focused on the data file containing the borough of Manhattan as I’m most familiar with it. The dataset has a separate row for each building complex in the city and about 80 columns of information for each one.
“Robo-investing” – using computer algorithms rather than humans to manage your investments – is a white-hot sector attracting lots of start-up cash.
There are now several companies here in the US promising that their algorithms can get more bang for your investment buck at a fraction of the price charged by traditional investment managers.
Managing your portfolio, diversifying your investments and handling your tax liabilities can all be done automatically 24/7.
And machines aren’t swayed by fear and greed, the primary emotions that often drive very poor investment decisions. They can crunch terabytes of data and take a global, long-term view, spreading your investments across geographies and asset classes, from bonds to equities, index funds to property.
… if you’re not careful, modelling has a nasty way of enshrining prejudice with a veneer of “science” and “math.”Cathy has consistently made another point that’s a corollary of her argument about enshrining prejudice. At O’Reilly, we talk a lot about open data. But it’s not just the data that has to be open: it’s also the models. (There are too many must-read articles on Cathy’s blog to link to; you’ll have to find the rest on your own.)
You can have all the crime data you want, all the real estate data you want, all the student performance data you want, all the medical data you want, but if you don’t know what models are being used to generate results, you don’t have much.
The backlash against unethical labor practices in the “collaborative sharing economy” has been overplayed. Recently, The Washington Post, New York Times and others started to rail against online labor brokerages like Taskrabbit, Handy, and Uber because of an utter lack of concern for their workers. At the recent Digital Labor conference, my colleague McKenzie Wark proposed that the modes of production that we appear to be entering are not quite capitalism as classically described. “This is not capitalism,” he said, “this is something worse.” 
But just for one moment imagine that the algorithmic heart of any of these citadels of anti-unionism could be cloned and brought back to life under a different ownership model, with fair working conditions, as a humane alternative to the free market model.
Take, for example, Uber’s app, with all its geolocation and ride ordering capabilities. Why do its owners and shareholders have to be the main benefactors of such platform-based labor brokerage? Developers, in collaboration with local, worker-owner cooperatives could design such a self-contained program for mobile phones.