Master cyber criminals, super-trojans, workforce shifts, advanced analytics and more – CBR talks to the experts about how 2017 could prove an even bigger, smarter year for artificial intelligence.
AI certainly arrived with aplomb in 2016 with chatbots, digital assistants, Pokemon, Watson, and DeepMind just some of the AI companies and tech bringing artificial intelligence to the masses. The opportunities, benefits and promise of the technology, so experts say, is vast – limitless even – so what can we expect in the coming year?CBR talked to the top AI experts about their artificial intelligence predictions for the new year, with 2017 already shaping up to be even smarter than 2016.
Artificial Intelligence Predictions for 2017:
The Year of the digital Moriarty
Ian Hughes Analyst, Internet of Things, 451 Research
“With so much data flowing from the interconnected world of IoT, higher end AI is being used to find security holes and anomalies in systems that are too complex for humans to control. Security breaches we have seen so far have been brute force ones, the equivalent of a digital crow bar.
“AI being used to protect is clearly a benefit, but this technology is increasingly available to anyone, replacing the digital crow bar with a virtual master criminal, 2017 might just see Holmes versus Moriarty digital intellects start to battle it out behind the scenes.”
Artificial Intelligence Predictions for 2017:
The Year Machines Steal more human jobs than ever before
Dik Vos, CEO at SQS
“We will continue to see a rise in digital technology over the coming years, and 2017 will be the year we see the likes of Artificial Intelligence (AI) and automated vehicles take the place of low-skilled workers.
With machines pushing humans out of a number of jobs including, logistics drivers and factory workers, I predict we will see an increased emphasis placed on the retraining of up to 30 per cent of our working population. People want and need to work and 2017 will see those workers who have lost their jobs through digitalisation, start to filter across a variety of other sectors including manufacturing and labour.”
Artificial Intelligence Predictions for 2017:
The Year of the Buzzword Mart
Hal Lonas, CTO at Webroot
“In 2017 we will see an explosion of companies shopping at Buzzword Mart. The growing attention paid to terminology like Artificial Intelligence and Machine Learning will lead to more firms incorporating “me too” marketing claims into their messaging. 
Prospective buyers should take these claims with a grain of salt and carefully check the pedigree and experience of firms claiming to use these advanced approaches. Buyers are rightfully confused, and it is difficult to compare, prove, or disprove efficacy in an ecosystem where market messaging is dominated by legacy or unicorn-funded voices. All too often we see legacy technology bolting barely-functional technology onto bloated and ill-architected heavy-weight solutions, leading to a poor end product whose flaws can range from bad user experience to security vulnerabilities.
“This rings especially true for security, where the distinction between legitimate machine learning trained threat intelligence and a second-rate snap-on solution can be the difference between leaking critical customer or IP data files, or blocking the threat before it reaches the network.”
Artificial Intelligence Predictions for 2017:
The Year of AI-as-a-service
Abdul Razack, SVP & Head of Platforms, Big Data and Analytics, Infosys
“AI-as-a-Service will take off: In 2016 AI was applied to solve known problems. As we move forward we will start leveraging AI to gain greater insights into ongoing problems that we didn’t even know existed. Using AI to uncover these “unknown unknowns” will free us to collaborate more and tackle new, interesting and life-changing challenges.”
Artificial Intelligence Predictions for 2017:
The Year CIOs Take the AI Helm
Graeme Thompson, SVP and CIO, Informatica
“With the accelerating pace of business, organisations need to deliver change and make decisions at a rate unheard of just a few years ago. This has made human-paced processing insufficient in the face of the petabytes and exabytes of data that are pouring into the enterprise, driving a rise in machine learning and AI.
“Whereas before, machines would be used to complete a few tasks within a workflow, now they are executing almost the entire process, with humans only required to fill in the gaps.
“Rewind 20 years and we used tools like MapQuest to figure out the shortest distance between two points, but we never would have trusted it to tell us where to go. Now, with new developments like Waze, many of us delegate the navigation of a journey entirely to a machine.
“Before long, humans will no longer be needed to fill the gaps. We’ll find that machines are fully autonomous in the case of driverless cars, for example, because they can store and make sense of much more information than humans can process. However, organisations capitalising on the benefits of AI and machine learning will have to ensure data quality to guarantee the accuracy of these fast responses. Un-validated or inaccurate data in a machine learning algorithm causes misleading insights or inaccurate actions when automated.
“In 2017, CIOs will be tasked with taking the helm of data driven initiatives and ensuring that data is clean enough to be processed by machines to drive fast and accurate insight and action.”
Author : ELLIE BURNS
