In the last few years, the field of artificial intelligence (AI) has taken tremendous scientific strides.
These include vast improvements in processing power and computational efficiency, along with empowering new insights into object identification, language, and deep learning.
What will they think of next?
Here’s a choice list of articles by AI experts exploring that very question.
By Sriram Raghavan, VP, IBM Research AI
In 2020, three themes will shape the advancement of AI: automation, natural language processing (NLP), and trust.
Broadly, we’ll see AI systems work more quickly and more easily for data scientists, businesses, and consumers through automation.
NLP will play a key role in enabling AI systems to converse, debate, and solve problems using everyday language.
And with each of these advances, we’ll see more transparent and accountable practices emerge for managing AI data, through tools ranging from explainability to bias detection.
By AI Trends Staff
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.
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.
VentureBeat, by Khari Johnson
AI is no longer poised to change the world someday; it’s changing the world now.
As we begin a new year and decade, VentureBeat turned to some of the keenest minds in AI to revisit progress made in 2019 and look ahead to how machine learning will mature in 2020.
We spoke with PyTorch creator Soumith Chintala, University of California professor Celeste Kidd, Google AI chief Jeff Dean, Nvidia director of machine learning research Anima Anandkumar, and IBM Research director Dario Gil.
AI won’t take your job, but it 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.
By Pedro Uria-Recio
In 2020 ethical guidelines for AI will start to be standardized in business and society and some of them will shape regulations.
The current General Data Protection Regulation (GDPR) focuses mainly on data security, privacy, and ownership.
AI ethics standards will go far beyond this covering avoidance of unfair biases, explainability, and interpretability of AI systems (instead of black-box machine learning modules), human oversight of AI systems, etc
AI will lead to trust in AI: In order to believe in AI, these systems must be trusted, fair and valued. We need to ensure that the public can be trusted in the technology and that its conclusions or recommendations are not biased or manipulated.
Throughout 2020, reliability-regulating components will be intertwined with the AI lifecycle to help us build, test, run, monitor, and certify AI applications works confidence, not just for performance. Just as with the rise of AutoAI – the use of AI to create AI – we will witness an increase in the use of AI in AI management.
This adoption will lead to the creation of reliable AI workflows in a variety of industries, especially those strictly regulated.
However, there is a flip side to this AI coin.
As stated by Stephen Hawking, “Artificial Intelligence is likely the best or worst thing to happen to humanity.”
And that’s yet to be seen!
It is very difficult to predict how AI technology will develop in the future and if it will ever become fully aware like human beings.
However, what we can predict is how AI will develop in the coming year and what new applications will become more common in society.
The increasing benefits of artificial intelligence and machine learning
Is an artificial intelligence future one that we can look forward to and trust to be working in our interest?
At the very least, the public needs to be certain that the technology is secure and that its conclusions or recommendations aren’t biased or manipulated.
Throughout 2020, components that regulate trustworthiness will be interwoven into the fabric of the AI lifecycle.
These will help developers and innovators build, test, run, monitor, and certify AI applications not just for performance but also for trust.
Researchers will explore utilising AI to govern itself while also deploying trust workflows across industries, especially those that are heavily regulated.
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