A major concern for our rights as consumers is the way that machines direct us according to their interests and not ours. Experts such as Dr Jonathan Cave warn about the growing influence of software machines on our lives. Cave says that software machines will make use of what they know about us to present information to us which may not be to our advantage. Because the search engines that we have used know a certain amount about us and our previous buying decisions, they are keen to exploit that by turning us into a buyer of something, by a process known as'filter bubbles' – a feedback loop where recommendations only reinforce existing patterns. As Dr Rupp states'if you are not paying then you are not the customer'. Thus if you are not paying for an internet technology such as Google or Facebook it is not acting in your interests, but rather in the interests of the customers who are paying to present information to you.

We won't have to wait until 2019 for our Blade Runner future, mostly because artificially intelligent robots already walk, roll and occasionally backflip among us. Some have wagged their way into our hearts while others have taken a more literal route. Both in civilian life and the military battlespace, AI is adopting physical form to multiply the capabilities of the humans it serves. As robots gain ubiquity, friction between these bolt buckets and we meat sacks is sure to cause issues. So how do we ensure that the increasingly intelligent machines we design share our ethical values while minimizing human-robot conflict?

When Ayanna Howard was a little girl, her favorite TV show was the Bionic Woman. Growing up, Howard was obsessed with creating robots. She earned her Ph.D. in Electrical Engineering and by the time she was 27 she landed her dream job at NASA's Jet Propulsion Laboratory (JPL). Howard leads a small team of engineers and scientists tasked with advancing the intelligence of robots for future Mars missions. In this video, Howard describes an experience early on in her career at JPL and how courage is a necessary part of the invention process.

The machine has been unveiled at the firm's Disney World resort where it will take part in a 25 minute show.

The most underappreciated application for the combination of augmented reality (A.R.) and artificial intelligence (A.I.) is persistent lie detection. Smartphones and smart glasses will soon support apps that show you in real time whether the person you're talking to is telling the truth or lying. Imagine how that will affect business meetings, sales presentations, job interviews and department status updates. Some 35 years ago, late-night talk show host Johnny Carson imagined what it would be like if politicians were hooked up to lie detectors.) Soon, you won't have to imagine it.

When it comes to Artificial Intelligence (AI), it pays to be ahead of the game. Russian President Vladimir Putin recently quipped that the nation that wins the AI war will be the ruler of the world, and his statement seems somewhat prophetic. As the nascent AI technology begins to take root in a variety of industries, early adopters are already well ahead of the curve in taking advantage of what promises to be the next major technology to revamp the face of the technical world. One of the most crucial areas for getting ahead of the game in the AI revolution is investing. When it comes to investment calculations and planning, analysts already use complex algorithms to seek to predict where markets will move. By adding AI to data source analysis, Mirocana, a state of the art investment platform, will move investors one step ahead of the game.

What exactly is artificial intelligence, and what does it mean for how we live and work? That was the topic of discussion at a recent hearing I chaired on "Digital Decision-Making," held before the Senate subcommittee that oversees Internet and telecommunications issues. Artificial intelligence, often referred to as AI, might sound straight out of a science fiction book or TV show, but it is becoming an increasingly common, if not instrumental, part of everyday life. AI is the technology that enables a machine to make a decision based on the data it has collected, such as when a smartphone gives driving directions around congested traffic or an e-mail system detects spam messages. Social media, online shopping, and preventing credit card fraud all have AI components.

The question over what to do about biases and inequalities in the technology industry is not a new one. The number of women working in science, technology, engineering and mathematics (STEM) fields has always been disproportionately less than men. What may be more perplexing is, why is it getting worse? It's 2017, and yet according to the American Association of University Women (AAUW) in a review of more than 380 studies from academic journals, corporations, and government sources, there is a major employment gap for women in computing and engineering. North America, as home to leading centres of innovation and technology, is one of the worst offenders.

This was a wild and tumultuous year in tech, with game-changing scandals, staggering displays of incompetence, and chin-scratching revelations. And while we may prefer to forget the dumpster fire that was the last 12 months, it's worth taking a moment to sit back, kick your feet up, pour a tall glass of something strong, and stroll down this perfectly decrepit memory lane. After all, heck, you made it through. And so, without further ado, here are the top 10 tech stories of the year, ranked. The news may be fake but that smile just has to be real.

With adaptive or risk-based authentication, organizations can leverage machine learning to build risk profiles based on employee information to strengthen their cybersecurity measures. A variety of inputs such as location, network reputation and device fingerprint make up the composite score to determine the risk potential of any sign-in attempt. Risk-based authentication then scores each login action based on established user profiles and adjusts the number of required authentication factors based on the level of suspicion. The higher the risk score, the more additional layers of authentication may be required, such as a one-time password to grant user access.