Top 6 AI Trends of 2020
As we enter a new decade, we also enter a new era of artificial intelligence, or AI.
While AI has seen widespread deployment in many sectors over the past several years, it still isn’t being used to its full potential. According to MIT’s Artificial Intelligence Global Executive Study and Research Report published in October last year, 40% of organizations putting money and resources into AI have yet to see business results from those investments.
In the upcoming year, we can expect several exciting developments and more holistic utilization of this cutting-edge technology. Read on to learn more about what 2020 has in store for AI.
1. “AI for AI”
“AI for AI” is a term coined by IBM, which was defined by the VP of IBM Research AI Sriram Raghavan as “using AI to help automate the steps and processes involved in the life cycle of creating, deploying, managing, and operating AI models to help scale AI more widely into the enterprise,” according to an article published by The Next Web last month.
In another article published by IBM in October 2019, they introduced a number of tools that implement AI for AI technology. Among these tools included Google’s AutoML, H20.ai’s H2O, and of course IBM’s own tool, AutoAI. AutoAI creates AI solutions for data science projects that allow for human intervention in the model, meaning that an engineer can take over any part of the process if they feel that their input will improve the model. We can expect the influx of these tools and improvements in their processes to take off in the next year as AI for AI continues to grow.
2. Hyperautomation
Another exciting development in AI predicted to really take off in 2020 is hyperautomation.
Since Gartner published its Top Ten Strategic Technology Trends for 2020 in October last year with hyperautomation at the top of the list, interest in the topic has skyrocketed as companies turn their attention to the trend. But what exactly does hyperautomation mean?
In their trends report, Gartner defines hyperautomation as “the combination of multiple machine learning (ML), packaged software and automation tools to deliver work.” To delve a little deeper, hyperautomation is based on robotic process automation (RPA) — which is used to replicate tasks — then goes a step beyond to bring automation to more knowledge-centered work that is otherwise normally performed by the human talent of an organization.
This has some exciting implications, including that hyperautomation can provide assistance in human actions through automated decision-making. In 2020, we can expect hyperautomation to advance as an emerging technology, bringing more automation to tasks previously considered beyond AI’s capabilities.
3. Soaring job demand
As the demand for AI solutions in business has increased over the past several years, demand for talent in the field has naturally followed.
2020 is no exception, as proven in LinkedIn’s 2020 Emerging Jobs Report published last month. At the very top of the list was Artificial Intelligence Specialist — boasting a 74% growth rate and a six-figure base salary. Robotics Engineer was a close second, with the third emerging position being Data Scientist, another role that heavily utilizes AI.
But proving the skill of this high-level discipline continues to be a challenge for companies and recruiters alike, which is where the next trend really shines.
4. Democratization
Referring back to Gartner’s Top 10 Strategic Technology Trends for 2020, there has been a major push for more simplified AI systems where it doesn’t matter whether you’re an expert or beginner in the technology — everyone can enjoy the benefits of automation.
This is great for both AI beginners — who Gartner coins as “citizen data scientists” and predicts will provide higher volumes of advanced analysis than professional data scientists — as well as experts in the field. Professionals can prove their skills on crowdsourced online AI platforms like ours, and companies can find the right talent for their projects on the same platform, too. With increased democracy of AI solutions, everyone wins.
5. Predictive text improvement
Predictive text entry uses AI to guess what you will write next in your sentence based on what’s already been written. The more inputs you and others provide it, the better the technology becomes at guessing what you want to say next.
The technology has been used by Gmail for over a year, and Google recently announced a beta version of predictive text for Google Docs called Smart Compose in a blog update they posted in November 2019.
With Google adopting the technology and boasting billions of users worldwide, their predictive text will have enormous amounts of input which will improve the quality of this yet unimpressive tool. Thus, we can expect better text prediction and its increased use in business applications over the next year.
6. AI ethics
AI is growing rapidly, and big players in the tech space are taking notice — as well as caution. While Elon Musk resigned from his position at AI ethics research group OpenAI in 2018, the organization is continuing to expand and promote the ethical use of AI, and they are not alone.
Efforts have been ramping up to ensure that AI abides by moral standards, including guidelines being set forth by the EU to ensure that AI is trustworthy, adheres to values, and is socially robust. Another example of standards-setting for the cutting-edge technology is California’s Consumer Privacy Act coming into effect this month, giving tech users the right to opt out of companies gathering their data and AI systems using it.
And these two are not the only protection systems going into effect — countries all over the world are considering or have already implemented laws protecting consumer data. These are big steps, and even though 2020 has only just started, it is already turning out to be a year where AI ethics is more relevant, adopted, and needed than ever.
