We all try our best to keep up with the news, particularly news that relates to our jobs. But life gets in the way–kids need to be fed, laundry needs to be done and Netflix needs to be watched. That’s why our team reads every AI article we can get our hands on to give you a weekly digest of the latest and greatest in artificial intelligence that you need to know.
Here are the top three articles to read this week before your next episode of Breaking Bad auto-starts.
1. Welcome to Machine Groupthink
In keeping up with AI, you may have heard of natural language processing, machine learning and neural networks. But, have you heard of machine teaching? In SingularityHub's latest article on AI, they break down the incredible intelligence that is machine teaching and how AI systems are getting smarter, faster.
For Tesla’s Model S car, all drivers are essentially “expert trainers.” By driving their cars and guiding them when necessary, the vehicles’ autonomous features improve. However, when one Model S learns from its driver, that information is shared with every other Model S on the road—hence, machine teaching. As a result, Tesla owners today are astonished at the rapid rate at which their vehicle’s driverless features are improving.
This practice of using group knowledge to develop AI is groundbreaking.
“Data is the fuel of machine learning, but even for machines, some data is hard to get—it may be risky, slow, rare, or expensive. In those cases, machines can share experiences or create synthetic experiences for each other to augment or replace data. It turns out that this is not a minor effect, it actually is self-amplifying, and therefore exponential.”
Consider the speed at which one driverless car could learn and navigate New York City. Now imagine one hundred driverless cars navigating that same city together, sharing what they learn. Through shared knowledge transferring, vehicles’ algorithms can improve so much quicker.
As machines begin to interact more with their environments and share that knowledge with other machines, the pace of development will continue to move at a rate that is hard to fathom.
2. AI Is The New Black
TechRepublic reported that in 2017, 61% of businesses implemented some sort of AI, up from just 38% in 2016. In the enterprise, the pressure of tech adoption is the driver of this with 71% of the 200 executives surveyed saying they their companies have strategies in place to push innovation.
"The time has come for every enterprise to come to grips with AI's impact and challenges, and begin to build a roadmap to harness its potential to transform businesses and industries."
Over the past year, enterprises have been trying out all types of AI and have seen a positive impact in the areas of business intelligence, finance, compliance, product management, and marketing and sales. The top solutions being implemented are predictive analytics (25%), machine learning (22%) and natural language processing (14%).
The executives went on to say that implementing AI has been most beneficial in their organizations for automating repetitive tasks, improving workforce productivity, and competing with peers.
Although some businesses and professionals would like to believe that the need for AI is only premature at this time, this report serves as a wake-up call. The importance of implementing AI is right in front of us and the sooner professionals realize that, the sooner their businesses can begin reaping the benefits.
3. Robots As Leaders?
AI is proving more capable of executing human tasks at a faster and more efficient rate. However, these are teachable abilities—hard skills. Is AI adept enough to also learn softer skills, like leadership and motivation, too? According to Harvard Business Review, yes and no.
There are many aspects that feed into effective leadership. The skills that can be taught, such as expertise, decisiveness, authority, and focus, can and will be picked up by machines, says HBR.
This will leave other skills—like humility, adaptability, vision, and constant engagement—for humans. This means in order to be a valuable leader, professionals need to start polishing the skills they can control.
“In an AI age characterized by intense disruption and rapid, ambiguous change, we need to rethink the essence of effective leadership,” the publication notes.
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