IBM researchers expect that three themes will shape the advancement of AI in 2020: automation, natural language processing (NLP), and trust.

The researchers expect to see AI systems work more quickly and more easily for data scientists, businesses, and consumers through automation. NLP is expected to play a key role in enabling AI systems to converse, debate, and solve problems using everyday language. And with each of these advances, more transparent and accountable practices are expected to emerge for managing AI data, through tools ranging from explainability to bias detection.

From this lens, IBM Research made the folowing five predictions for AI in 2020:

• AI will understand more, so it can do more: The more data AI systems have, the faster they will get better. But AI’s need for data can pose a problem for some businesses and organizations that have less data than others. That doesn’t mean they can’t count on the support of AI. During the coming year, more AI systems will begin to rely on “neuro-symbolic” technology that combines learning and logic. Neuro-symbolic is the ticket to breakthroughs in technologies for NLP, helping computers better understand human language and conversations by incorporating common sense reasoning and domain knowledge. Such breakthroughs will soon help businesses deploy more conversational automated customer care and technical support tools – while requiring much less data to train the AI.
• AI will change how you work: AI will continue to impact the workplace for years to come. But the fear that humans will lose their jobs to machines is unjustified. Rather, AI will transform the way people work, through automation. New research from the MIT-IBM Watson AI Lab shows that AI will increasingly help us with tasks such as scheduling, but will have a less direct impact on jobs that require skills such as design expertise and industrial strategy. Expect workers in 2020 to begin seeing these effects as AI makes its way into workplaces around the world; employers have to start adapting job roles, while employees should focus on expanding their skills.
• AI will engineer AI for trust: To trust AI, these systems have to be reliable, fair, and accountable. It should be ensured that the public can be certain that the technology is secure and that its conclusions or recommendations aren’t biased or manipulated. During 2020, components that regulate trustworthiness will be interwoven into the fabric of the AI lifecycle to help us build, test, run, monitor, and certify AI applications for trust, not just performance. Just like with the rise of AutoAI – the use of AI to create AI – expect to see the rise of AI to govern AI. This adoption will create trustworthy AI workflows across industries, especially those that are heavily regulated.
• AI’s appetite for energy demands greener tech: Data centers are the linchpins of the modern world. They are also the underpinning of artificial intelligence and account for as much as 2% of the world’s total energy use. Demand for cloud computing and AI won’t go away, so expect to see increased efforts in 2020 that look to make AI tech more sustainable. This includes creating new materials, like “transition-metal oxides” that make more flexible devices, new chip designs with both analog and mixed-signal processing, and new software techniques based on approximate computing, that all aim to support growing AI workloads while reducing its carbon footprint.
• AI-powered lab assistants will discover new materials: For more than two centuries, the synthesis of organic molecules has been one of the key aspects of research in industrial chemistry. As a result, the world has life-saving drugs and synthetic fibers. Yet, researchers still struggle to map the hundreds of thousands of possible reactions when creating different molecules. The sheer volume of information means it’s possible for a scientist to remember a few dozen reactions in their field, but it’s impossible to be an expert in everything. Now, they may not have to. IBM is working on AI tools that can predict millions of chemical reactions – both backwards and forwards – as well as synthesize molecules in the cloud. Expect 2020 to deliver significant growth in harnessing the power of AI and automation to spur breakthroughs in material discovery and development.