An automated machine learning platform called Auto Tune Models (ATM) from MIT and Michigan State University uses cloud-based, on-demand computing to speed data analysis. -MIT and Michigan State University, 2017
ATM was able to deliver a solution better than the one humans had come up with 30% of the time, and could do this 100x faster. -MIT and Michigan State University, 2017
This is an interesting podcast talking about a social application of data analytics to fix the bail system of New Jersey.
In New Jersey, defense attorneys, judges, and prosecutors got together to try to reform a system that treated poor defendants so differently from rich ones. In the end: they got rid of bail.
… The Risk Assessment Algorithm predicts the probability of failing to show up in courts and the probability of committing to another crime before the next trial in a 1-to-6 scale. It considers the following factors
- Does the person have a priori conviction of violance within the past x years?
- Have the person had failed to appear in courts in priori cases?
- The age of the person when the crime was committed, and others.
… Data shows that, if your age was under 23 when committing a crime, the person is more likely to commit a new crime than an older person.
… Some specific factors such as race and wealth are excluded in order to prevent bias, whereas keeping the forecast reliable.
… Since the introduction of the algorithm, people are detained with real information. The jail population is reduced by almost 30%. The result is very profound.
Reference: New Jersey Bails Out
Amazon, whose Prime service claims more than 70% of upper-income households in the US — those earning more than $112,000 a year — is suddenly going after customers on government assistance who earn less than $15,444 a year for a one-person household.
The retailer on Tuesday announced it would slash the cost of its monthly Prime membership nearly in half, to $5.99 a month, for customers who have an electronic benefit transfer card, which is used for government assistance like the Supplemental Nutrition Assistance Program, better known as food stamps.
Political analyist concluded ‘Hillary doesn’t fit the bill’ partly because she lacked Barack Obama’s charisma. Allan Lichtman, a political analyst who has correctly predicted the results of every presidential election since 1984, correctly foresaw that Mr Trump would be the 45th US President.
Unlike many experts who fixated on Mr Trump’s controversial campaign when assessing the election outcome, Professor Lichtman’s calculations largely focused on the incumbent party’s potential for another victory based on 13 key assessments. The system entails “mathematically and specifically” measuring the performance of the party in office. It is a historically based prediction system. He derived the system by looking at every American presidential election from 1860 to 1980.
One of his keys is whether or not the sitting president is running for re-election, and right away, [the Democrats] are down that key.
Another one of his keys is whether or not the candidate of the White House party is, like Obama was in 2008, charismatic. Hillary Clinton doesn’t fit the bill.
Check out the articles below for details of his calculation:
- Donald Trump’s win was predicted by Allan Lichtman — the US election expert who has called every result since 1984
- Keys to the White House
Earlier this week, CBS News profiled five strange and unexpected things that have correctly predicted the results of the presidential election for decades. Now, it seems, three of those five predictors were right — forecasting Donald Trump would be the 45th president of the United States.
- A mystic monkey in Changsha, China.
- The “Halloween mask index” had Donald Trump ahead of Hillary Clinton, 55 to 45 percent.
- The American University professor Allan Lichtman.