Lifeboat Foundation

Everyone knows prevention is better than a cure, and that’s as true for law enforcement as it is for medicine. But there’s little evidence that a growing trend towards “predictive policing” is the answer, and it could even bake in racial bias.

Police departments faced with tight budgets are increasingly turning to machine learning-enabled software that can sift through crime data to help predict where crimes are likely to occur and who might commit them.

Using statistics in law enforcement is nothing new. A statistical system for tracking crime called Compstat was pioneered in New York in 1994 and quickly became popular elsewhere. Since then, crime has fallen 75 percent in New York, which has been credited by some to the technology. But while Compstat simply helped identify historical hotspots, “predictive policing” uses intelligent algorithms to forecast tomorrow’s hotspots and offenders.

Continue reading “Could Predictive Policing Lead to a Real-Life Minority Report?” »

SWARM still only restricts itself to sample sets/ group representation of the population. And, when we place AI in this mix; I get concerned still where daily lives are impacted by decisions coming out from this model. For example, I would hate to see laws and policies rely on SWARM data reasoning as Laws and Policies often have special exceptions that Judges and Policy makers must still have the ability to call not AI with SWARM.

US intelligence is investing millions of dollars in a global research effort to boost analytical thinking by unlocking the reason in crowds.

Teaching robots to communicate more effectively with humans will allow for a smoother transition into a more automated workplace.

Top teams will compete in a simulated Mars mission.

Nice.

Summary: Newly developed software allows researchers to study synaptic plasticity in dendritic spines.

Source: max planck florida institute for neuroscience.

Continue reading “New Software Automates Brain Imaging” »

Some middle-income jobs have 97% chance of being replaced, study finds.

I had thought my job was safe from automation—a computer couldn’t possibly replicate the complex creativity of human language in writing or piece together a coherent story. I may have been wrong. Authors beware, because an AI-written novel just made it past the first round of screening for a national literary prize in Japan.

The novel this program co-authored is titled, The Day A Computer Writes A Novel. It was entered into a writing contest for the Hoshi Shinichi Literary Award. The contest has been open to non-human applicants in years prior, however, this was the first year the award committee received submissions from an AI. Out of the 1,450 submissions, 11 were at least partially written by a program.

Here’s an excerpt from the novel to give you an idea as to what human contestants were up against:

Continue reading “Japanese AI Writes a Novel, Nearly Wins Literary Award” »

Forget super-AI. Crappy AI is more likely to be our downfall, argues researcher.

The past couple of years have been a real cringe-y time to be an AI researcher. Just imagine a whole bunch of famous technologists and top-serious science authorities all suddenly taking aim at your field of research as a clear and present threat to the very survival of the species. All you want to do is predict appropriate emoji use based on textual analyses and here’s Elon Musk saying this thing he doesn’t really seem to know much about is the actual apocalypse.

It’s not that computer scientists haven’t argued against AI hype, but an academic you’ve never heard of (all of them?) pitching the headline “AI is hard” is at a disadvantage to the famous person whose job description largely centers around making big public pronouncements. This month that academic is Alan Bundy, a professor of automated reasoning at the University of Edinburgh in Scotland, who argues in the Communications of the ACM that there is a real AI threat, but it’s not human-like machine intelligence gone amok. Quite the opposite: the danger is instead shitty AI. Incompetent, bumbling machines.

The machine-learned smarts that enable Microsoft’s Skype Translator, Bing and Cortana to accomplish tasks such as translating conversations, compiling knowledge and understanding the intent of spoken words are increasingly finding their way into third-party applications that people use every day.

These advances in the democratization of artificial intelligence are coming in part from Microsoft Cognitive Services, a collection of 25 tools that allow developers to add features such as emotion and sentiment detection, vision and speech recognition, and language understanding to their applications with zero expertise in machine learning.

Continue reading “Microsoft Cognitive Services push gains momentum” »