Brain drain from academics is hurting economy

The study, the first of its kind, was conducted by researchers at the University of Rochester. They found that over the last 15 years, 153 artificial intelligence professors in North American universities left their posts for industry. Another 68 moved into industry while retaining part-time roles with their universities.


SAN FRANCISCO: For years, big tech companies have used huge salaries, bonuses and stock packages to lure artificial intelligence experts out of academia. Now, a study released on Friday says that migration has hurt the post-college prospects of students.

The study, the first of its kind, was conducted by researchers at the University of Rochester. They found that over the last 15 years, 153 artificial intelligence professors in North American universities left their posts for industry. Another 68 moved into industry while retaining part-time roles with their universities.

From 2004 to 2009, 26 university professors moved into industry. In 2018 alone, 41 professors made the move. The exponential rise in departures over the last decade and a half indicates that the trend will continue. The talent shift could accelerate the development of artificial intelligence inside tech giants like Google, Microsoft, Amazon and Apple.

But at the universities the professors left behind, graduating students were less likely to create new AI companies. When they did, they attracted smaller amounts of funding, according to the study. The effect was most pronounced in the field of “deep learning,” a technology that has become a crucial part of new AI systems.

In time, the brain drain from academia could hamper innovation and growth across the economy, the study argued. “The knowledge transfer is lost, and because of that, so is innovation,” said Michael Gofman, a professor of finance at the University of Rochester and one of the authors of the study.

Deep learning is driven by “neural networks,” complex mathematical systems that can learn tasks on their own by analysing vast amounts of data. By pinpointing patterns in thousands of dog photos, for instance, a neural network can lear n to recognise a dog.

Big tech companies have hired many of the academics who specialized in the technique. Three longtime academics recently won the Turing Award — often called the Nobel Prize of computing — for their work on neural networks. Two have moved into industry, one to Google and the other to Facebook.

Tech and automobile industry’s interest in artificial intelligence of all kinds has increased, according to the study. Google and DeepMind, both owned by Alphabet, have hired 23 professors. Amazon has hired 17 professors. Microsoft has hired 13 professors. And Uber, Nvidia and Facebook have each hired seven.

Tech companies disagree with the notion that they are plundering academia. A Google spokesman, for example, said the company is an enthusiastic supporter of academic research.

The study found that students most affected by the departures were those who graduated four to six years later, meaning they probably had little interaction of the departing professors. At any given university, a significant increase in the number of departing professors reduced the number of AI entrepreneurs by 13%.

Experts are split on whether a decline in the startup economy will harm the progress of AI. But many agree that university funding should be increased to ensure that the next generation is properly educated.

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AI could improve police paperwork: MHA think tank

BPRD’s futuristic vision for law enforcement , especially in smart cities, Prime Minister Narendra Modi’s ambitious project, is part of a concept note the body has drafted.
In a recent interview with The Economist, author Malcolm Gladwell, too discusses the importance of AI in the criminal justice system.(HT image)


The use of Artificial Intelligence in police paperwork, including charge sheets could remove flaws and prejudices from creeping into investigations, India’s Bureau of Police Research & Development (BPRD), a think-tank of the ministry of home affairs (MHA), believes.

BPRD’s futuristic vision for law enforcement , especially in smart cities, Prime Minister Narendra Modi’s ambitious project, is part of a concept note the body has drafted.

“A machine-learning algorithm can generate chargesheets specific to an incident with complete legal validity without any exclusions or non-conformity. This allows minimal manual intervention; hence the scope for malicious intent is not there in any way and the ability of the legal system to prosecute to the fullest extent of the law is always available. In the charge sheet, references from other judgements as well as other outcomes can also be included to make it more effective,” reads the note, a copy of which has been seen by HT.

Asserting that AI based systems have outperformed lawyers as well as judges in some cases, the BPRD note adds: “A neural network based system over a period of time can also create sensor based inputs in order to predictively allow for the analysis of outcome of cases as well, helping speed up the judicial process. The consequent burden on the policing system goes down”.

In a recent interview with The Economist, author Malcolm Gladwell, too discusses the importance of AI in the criminal justice system. Citing an example of judges taking bail decisions, Gladwell says, “..Defendants stand in front of the judge, the judge has to decide whether I released this person until the trial or I put the person in jail. Are they likely to commit another crime in the interim? That’s an extremely difficult decision to make. And when we look at how effective judges are in predicting the dangerousness of the defendant, they are not very good at it. But look how the machine learning algorithm tends to do better, actually much better than the judge. So there is an instance where we have clear evidence that a disembodied computer can be more accurate in making a prediction about the human being than a judge.”

Gladwell, however, also argues that there is a need to combine both the decision making of humans and AI, a view that many proponents of AI have also advocated.

According to BPRD, AI models coupled with crime mapping can be developed “to analyse crime patterns and identify hotspots which act as a useful tool for predictive and preventive policing”.

The police can also use AI based on algorithmic software at a crime scene for immediate recognition of perpetrator (s) based on modus operandi, pattern of crime/criminals in the area, biometric data, forensic data etc, the note claims. The BPRD note cites the example of San Francisco based Deep Science AI which has developed AI Surveillance (AIS) platform which uses deep learning to identify real people concealing their faces/firearms of intruders.

AI can also be used to manage traffic in smart cities, BPRD has suggested in its note.

To be sure, all this needs integrated data on video surveillance of public places, a wide CCTV camera network, sensors just about everywhere, databases of criminals, information on public transport, real-time tracking of events, and other such, the note admits. It also adds that privacy concerns need to be factored in while using such technologies.

When asked how AI can help police smart cities, Tarun Wig, co-founder of Innefu, a data analytics and cyber security company which provides predictive intelligence systems to various government institutions said: “The AI based system will read the text on a particular case which has to be charge sheeted and extract data on similar charges and relevant law provisions. It can read the type of crimes and tell police how to use its resources”.

BPRD and MHA officials did not respond to queries seeking comment on the concept note.

Source: https://www.hindustantimes.com/india-news/ai-could-improve-police-paperwork-mha-think-tank/story-ntYcMOFRvWX8ij4SRlgR4K.html (Accessed on September 13, 2019)