NEW YORK--Siri evaded my question for what took Apple's voice assistant so long to get onto the Mac.

The magic and frustration of voice assistants and artificial intelligence when it comes to accessibility. A lot has been said recently about Apple's prospects in artificial intelligence and machine learning. One aspect of the discussion that I haven't seen considered is the accessibility ramifications of artificial intelligence in assistants like Siri. I've long been a proponent of voice-driven interfaces as assistive technology, which makes Siri's slow development all the more frustrating. This is particularly true when it comes to Siri understanding you if you have trouble speaking.

Customer behaviour and the development of new technology are inextricably linked, and no technology is poised to impact our daily lives more than artificial intelligence (AI). AI is not a single technology but a convergence of statistical models, algorithms and approaches that make software'smart', whereby it starts to mimic human thinking processes. AI is already present in our digital lives, powering everything from dynamic product pricing on Amazon to song recommendations on Spotify – but we are still only at the dawn of witnessing its power. Perhaps the most impactful uses of AI will be in eCommerce – an area of immense growth in its own right. We are starting to see applications of AI via cognitive technology, a simulation of human thought processes, to respond to natural human language.

As an AI, Scarlet works on observing patterns, connecting the dots and inferring new insights. So yes, over time, she will build up a context of your behaviors and, we're working towards this, she will suggest things she could do for you. That will take us a moment. We're finding an interesting challenge there in that most content providers have created material that is designed to be seen on a screen with accompanying pictures. We need them to write the words that evoke the visual so she can describe it to you.

After great promise in the 1960s that machines would soon think like humans, progress stalled for decades. Only in the past 10 years or so has research picked up, and now there are several popular products on the market that do a decent job of at least recognizing spoken speech. For Björn Schuller, full professor and head of the chair of Complex and Intelligent Systems at the University of Passau, Germany, who grew up watching Knight Rider--a television show about a car that could talk--this is the fulfillment of a childhood fantasy. Schuller is a World Economic Forum Young Scientist who will speak at the World Economic Forum's Annual Meeting of the New Champions in Tianjin, China, from June 26 to 28.He recently spoke about the possibility of machines soon tuning in to human language quirks, behavior and emotion. How did you get interested in machine intelligence and speech recognition?

The Amazon Echo is an unlikely hit. After all, the world's largest online retailer hasn't always won its bets on hardware. And a gadget that relies solely on voice? Yet Amazon has by one estimate sold some 3 million of the squat cylinders since the Echo launched in November, 2014. The company doesn't share sales data, but it did say Alexa, the voice-activated software that powers Echo, is active in millions of places, including smartphone apps and other Amazon gadgets.

They can still have trouble understanding simple commands to play music or look up directions, though, especially in noisy places. Rather than focusing on cleaning up the audio signal that captures your voice, Israeli startup VocalZoom thinks it might be possible to make all kinds of speech-recognition applications work a lot better by using a tiny, low-power laser that measures the itty-bitty vibrations of your skin when you speak. The company, which has raised about 12.5 million in venture funding thus far, is building a sensor with a small laser that it says will initially be built into headsets and helmets; there, it will be used alongside existing speech-recognition technologies that rely on microphones in order to reduce overall misunderstandings. VocalZoom founder and CEO Tal Bakish thinks it will first be used for things like motorcycle helmets or headsets worn by warehouse workers--you might use it to ask for directions while riding your Harley, for instance. A Chinese speech-recognition company called iFlytek plans to have a prototype headset ready at the end of August.

Everyone wants to keep ahead of the technology curve, whether it's being'in-the-know' or as a vital part of your business, to allow for effective future planning or perhaps to start building systems and products based on that technology. So how do you know what that next big thing will be? Were people betting on touch interfaces in 2002? Not me, I was in a Macromedia Flash phase and couldn't possibly imagine anything beating a vector shape moving across the screen at 12 frames per second. I am not that same guy anymore.

In the last couple of years, magic started happening in AI. Techniques started working, or started working much better, and new techniques have appeared, especially around machine learning ('ML'), and when those were applied to some long-standing and important use cases we started getting dramatically better results. For example, the error rates for image recognition, speech recognition and natural language processing have collapsed to close to human rates, at least on some measurements. So you can say to your phone: 'show me pictures of my dog at the beach' and a speech recognition system turns the audio into text, natural language processing takes the text, works out that this is a photo query and hands it off to your photo app, and your photo app, which has used ML systems to tag your photos with'dog' and'beach', runs a database query and shows you the tagged images. There are really two things going on here - you're using voice to fill in a dialogue box for a query, and that dialogue box can run queries that might not have been possible before.

You, client! may not be science fiction for much longer. On both sides of the Atlantic and elsewhere, British authors Richard and Daniel Susskind and others predict Artificial Intelligence is on the cusp of changing the legal profession more than any other technology. We've already seen the transformation triggered by word-processing, the Internet and e-mail, but the high hourly rates of legal professionals and the exorbitant expense of court time demand more reform. The B.C. government has been an early adopter of software solutions and the province already has a handful of dispute-resolution and legal platforms intended to make access to legal services and justice easier and cheaper. The next development, however, is heralded by the arrival of "digital legal advisers" -- the progeny of Deep Blue, which destroyed the chess hegemony of humanity, and Watson, which ruined Jeopardy!