MIT Sloan Associate Professor Tauhid Zaman
From The Conversation
Nearly two-thirds of the social media bots with political activity on Twitter before the 2016 U.S. presidential election supported Donald Trump. But all those Trump bots were far less effective at shifting people’s opinions than the smaller proportion of bots backing Hillary Clinton. As my recent research shows, a small number of highly active bots can significantly change people’s political opinions. The main factor was not how many bots there were – but rather, how many tweets each set of bots issued.
My work focuses on military and national security aspects of social networks, so naturally I was intrigued by concerns that bots might affect the outcome of the upcoming 2018 midterm elections. I began investigating what exactly bots did in 2016. There was plenty of rhetoric– but only one basic factual principle: If information warfare efforts using bots had succeeded, then voters’ opinions would have shifted.
I wanted to measure how much bots were – or weren’t – responsible for changes in humans’ political views. I had to find a way to identify social media bots and evaluate their activity. Then I needed to measure the opinions of social media users. Lastly, I had to find a way to estimate what those people’s opinions would have been if the bots had never existed.
John Roberts, MIT Sloan Visiting Professor
From Entrepreneur Magazine
One might well ask, “What do micro-entrepreneurs in urban and slum neighborhoods across Cape Town, South Africa have to learn from the elite business schools of the world? It turns out that the answer to this question is: “Plenty.”
I recently had the honour of being Chairman of Judges of the prestigious Gary Lilien Practice Prize given by the INFORMS Society for Marketing Science, in conjunction with the Marketing Science Institute and the European Marketing Academy. The award winning study proves that the tools of marketing science can make a major positive impact in helping to grow disadvantaged economies like the ones in Cape Town.
MIT Sloan Sr. Lecturer John Reilly
From Fortune Magazine
Is the Green New Deal (GND) a liberal pipe dream, or is it an opening for an economically viable, bipartisan climate change solution?
The program put forward by Rep. Alexandria Ocasio-Cortez (D-N.Y.) and her team reimagines the U.S. as a nation with no carbon emissions, full employment, a fair and equal economy, and justice for all. This GND proposal pairs massive government spending with quantitative easing by the Federal Reserve to achieve these aims. Since we can just print money, the argument goes, it would cost nothing.
Not so fast. Whereas deficit spending and a Fed stimulus package are good policies in a deep recession, we are now near full employment. For a Green New Deal to work now, we will need to pay for any federal investment with higher taxes. Moreover, that investment should be rolled out gradually.
MIT Sloan School of Management Senior Lecturer, Senior Advisor MIT Media Lab, Gary Gensler
After this year’s wild market ride and so many failed projects, what might Satoshi Nakamoto’s innovative “Bitcoin: A Peer-to-Peer Electronic Cash System” mean for money and finance in 2019 and beyond?
Satoshi’s innovation – the use of append-only timestamped logs, secured by cryptography, amongst multiple parties, forming consensus on a shared ledger – needs to be taken seriously. The resulting blockchains of data can form widely verifiable peer-to-peer databases.
For any chance of a lasting role in the long evolution of money, though, blockchain applications and crypto assets have to deliver real economic results for users. And while bringing the crypto finance markets within public policy norms is critical, the greatest challenge remains the seriousness of commercial use cases.
A bunch of hype masquerading as fact won’t do it.
What We’ve Learned
Blockchain technology and crypto tokens provide an alternative means to move value on the Internet without relying upon a central intermediary. They promise the potential to lower verification and networking costs, ranging from censorship, privacy, reconciliation and settlement costs to the costs of jump starting and maintaining a network.
MIT Sloan Senior Lecturer Sharmila Chatterjee
From Boston Business Journal