The word "trust" pops up a lot in conversations about human-robot interactions. In recent years, it's crossed an important threshold from the philosophical fodder of sci-fi novels into real-world concern. Robots have begun to play an increasing role in life and death scenarios, from rescue missions to complex surgical procedures. But the question of trust has largely been a one-way street. Should we trust robots with our lives?

Longer term, who knows the fate of the human agent. There is certainly plenty of impetus for automation, but for now it can seem like a cool gimmick (see the Henn na Hotel). If used on any scale, AI has to be proven to definitively ease the customer journey and ultimately grow revenue.

On Thursday, March 9th, the Federal Trade Commission (FTC) hosted a forum on the consumer implications of recent developments in artificial intelligence (AI) and blockchain technologies. This was the FTC's third forum on issues in FinTech. Previous FinTech Forums covered marketplace lending and crowdfunding and peer-to-peer payments. In opening remarks, the FTC acknowledged the benefits of technological developments in AI and blockchain technologies: AI promises better decision-making and personalized consumer technologies, while blockchain technologies would increase the efficiency of financial transactions and eliminate the need for the middleman, among other benefits. But, the FTC stressed that advancements in these technologies must be coupled with an awareness of and active engagement in identifying and minimizing associated risks.

When I first heard of predictive analytics, machine learning, and cognitive security, I was skeptical. I am an engineer at heart and condition-based maintenance was the only way, I thought, to effectively look at predictive maintenance. You start with the physical asset, you deploy sensors to monitor critical components, and you analyze the data. The thing is, this approach is expensive and time-consuming. Sensors need to be deployed and installed on existing equipment, software to collect, store, and process the data needs to be integrated, O&M teams need to be trained on the technology, and the software needs to be constantly updated.

Finding a job can often prove to be a full-time responsibility in and of itself. Whether you're seeking employment or recruiting workers to join your ranks, the time lost finding the ideal candidate can often translate to reduced productivity, which can also mean less money in your pocket and more stress. To level the playing field in a time when virtually everything else is already being automated, startup Opportunity has become the first networking site to integrate artificial intelligence into its platform. Utilizing the advanced technology to streamline many filters companies often search for, the hiring platform screens for personality, previous work, skill sets, location and other such requirements, refining the way companies and prospective employees connect. To understand how radically new hiring practices might emerge due to these powerful algorithms, PSFK sat down in an exclusive interview with the company's CEO and Co-founder Janis Krums.

Once limited to the realm of fiction, AI is now the technology shaping our world more than ever before. Montreal is at the center of this movement, with some saying it could become the Silicon Valley of AI. This may come as a surprise with all the other tech research and startup hubs out there. What does Montreal have that they don't? As it turns out, the largest concentration of independent AI researchers in the world.

Today, 38% of enterprises are already using artificial intelligence (AI), growing to 62% by 2018.

Turns out, machines can learn. And while that may mean the fall of man, it also means self-driving cars and better Netflix recommendations. Machine learning is a type of artificial intelligence (AI) that gives computers the ability to learn without being explicitly programmed. The implications of that are pretty massive: it means that a developer doesn't need to know, for example, how to program a computer to drive a car. But that developer can use a series of complex algorithms to program the computer to teach itself how to drive a car.

Despite partial success, communication has remained impossible for persons suffering from complete motor paralysis but intact cognitive and emotional processing, a state called complete locked-in state (CLIS). Based on a motor learning theoretical context and on the failure of neuroelectric brain–computer interface (BCI) communication attempts in CLIS, we here report BCI communication using functional near-infrared spectroscopy (fNIRS) and an implicit attentional processing procedure. Four patients suffering from advanced amyotrophic lateral sclerosis (ALS)--two of them in permanent CLIS and two entering the CLIS without reliable means of communication--learned to answer personal questions with known answers and open questions all requiring a "yes" or "no" thought using frontocentral oxygenation changes measured with fNIRS. Three patients completed more than 46 sessions spread over several weeks, and one patient (patient W) completed 20 sessions. Online fNIRS classification of personal questions with known answers and open questions using linear support vector machine (SVM) resulted in an above-chance-level correct response rate over 70%.

If you want to become the world's first person to have a net worth with 12 zeros -- or $1 trillion -- Mark Cuban says artificial intelligence is your industry. Cuban, a billionaire entrepreneur and owner of the Dallas Mavericks, spoke at the SXSW festival in Austin, Texas this past weekend, claiming AI held untold wealth for anyone clever enough to tap its true potential. "I am telling you, the world's first trillionaires are going to come from somebody who masters AI and all its derivatives and applies it in ways we never thought of," Cuban said. The person closest to becoming a trillionaire, at least according to public financial records, is Bill Gates, although he is still about $915 billion short of the title. Some research suggests Gates will become the first trillionaire by the mid-2040s just by virtue of his accumulating wealth.