Artificial Intelligence was everywhere in 2018 and don’t expect the hype to die down over the next 12 months with the coming year’s advancements and innovation to bring about huge fundamental changes to a wide range of industries.
There is absolutely no uncertainty there will be more astonishing breakthroughs in 2019. This is because the expectations of changes to business and society in which AI promises (or in some cases threatens) to bring about, go beyond anything dreamed up during previous technological revolutions.
AI points towards a future where machines not only do all of the physical work they have done since the industrial revolution, but also the “thinking” work such as planning, strategizing and making decisions.
The jury is still out on whether this will lead to a glorious utopia with humans free to spend their lives following more meaningful pursuits. This is rather than on those which economic necessity dictates they dedicate their time, or to widespread unemployment and social unrest.
We probably won’t arrive at either of those outcomes in 2019, but it is a topic which will continue to be hotly debated. In the meantime, here are three things that we can expect to happen in 2019.
1. Increased Automation
In 2018, most organisations spent time trying to gain a better understanding of what AI can and can’t do for their business operations, where could it be deployed and show fast rewards? This year, it is likely that a lot of major corporations are going to be moving ahead with global deployment in order to reap the benefits of increased automation.
In financial services, vast real-time logs of thousands of transactions per second are routinely parsed by machine learning algorithms. Retailers are proficient at grabbing data through receipts and loyalty programmes, and feeding it into AI engines to work out how to get better at selling us things. Manufacturers use predictive technology to know precisely what stresses machinery can be put under and when it is likely to break down or fail.
In 2019, we will see growing confidence that this smart, predictive technology, bolstered by learnings has picked up in its initial deployments and can be rolled out to wholesale across many business’s operations. We are also likely to see an increase in businesses using their data to generate new revenue streams.
Becoming a source of data-as-a-service has been transformational for businesses such as John Deere, which offers analytics based on agricultural data to help farmers grow crops more efficiently. In 2019, more companies will adopt this strategy as they come to understand the value of the information they own.
2. Job Creation.
Artificial intelligence plays a part in preventing human errors, but AI also still needs human oversight to prevent its own errors. In saying that, there is a valid concern that even as AI saves lives and helps businesses thrive, it will destroy livelihoods. Without a doubt, AI is taking over jobs once done by humans. However, it is widely believed that in 2019 at least, AI will create more jobs than it destroys.
While 1.8 million jobs will be lost to automation – with manufacturing in particular singled out as likely to take a hit – 2.3 million will be created. In particular, Gartner’s report finds that these jobs could be focused on education, healthcare and in the public sector.
A likely driver for this disparity is the emphasis placed on rolling out AI in an “augmenting” capacity when it comes to deploying it in non-manual jobs. Warehouse workers and retail cashiers have often replaced wholesale by automated technology.
When it comes to doctors and lawyers, AI service providers have made concerted effort to present their technology as something which can work alongside human professionals, assisting them with repetitive tasks while leaving the “final say” to them.
This means those industries benefit from the growth in human jobs on the technical side – those needed to deploy the technology and train the workforce on using it – while retaining the professionals who carry out the actual work.
For the financial services, the outlook is perhaps slightly grimmer. Some estimates, such as those made by former Citigroup CEO Vikram Pandit in 2017, predict that the sector’s human workforce could be 30% smaller within five years. With back-office functions increasingly being managed by machines, we could be well on our way to seeing that come true by the end of next year.
It is obvious that we as a society cannot start deploying and using intelligent systems, machine learning solutions or cognitive computing platforms if their reasoning is blurred.
We must try to understand the way Artificial Intelligence works. This may be difficult, as what makes AI particularly useful is its ability to think and draw conclusions that are extremely difficult or maybe even impossible for human cognition to grasp.
However, building trust in AI systems isn’t just about reassuring the public. Research and business will also benefit from openness which exposes bias in data or algorithms. Reports have even found that companies are sometimes holding back from deploying AI due to fears they may face liabilities in the future, if current technology is later judged to be unfair or unethical.
In 2019, we are likely to see an increased emphasis on measures designed to increase the transparency of AI. This year IBM unveiled technology developed to improve the traceability of decisions into its AI OpenScale technology.
This concept gives real-time insights into not only what decisions are being made but how they are being made, drawing connections between data that is used, decision weighting and the potential for bias in information.
The General Data Protection Regulation, put into action across Europe last year, gives citizens some protection against decisions which have “legal or other significant” impact on their lives made solely by machines. While it isn’t yet a blisteringly hot political potato, its prominence in public discourse is likely to grow during 2019, further encouraging businesses to work towards transparency.