At the Marketing AI Institute, we read dozens of articles on artificial intelligence every week to uncover the most valuable ones for our subscribers and we curate them for you here. We call it 3 Links in 3 Minutes. Enjoy!
Talk about the rise of artificial intelligence is usually accompanied by bleak predictions of the number of jobs it will replace. But according to MIT Sloan Management Review, that’s only part of the story.
For businesses planning to leverage AI solely for efficiency, headcount may drop. However, research from McKinsey Global Institute found that for companies using AI to drive innovation, an increase in employees is actually more likely.
This is possible because innovation-focused early adopters of AI position themselves for growth, which tends to stimulate employment.
MIT Sloan’s research shows that the profitability of these early adopters will grow 8% faster than that of the average company by 2030. Revenue will grow 4% faster and the number of employees will increase 2.2% faster.
It was only seven years ago that IBM Watson debuted on Jeopardy! and since then, the world has already changed tremendously.
Today, we use artificial intelligence every single day, perhaps without even noticing. Whether it’s talking to a smart speaker like Amazon’s Alexa or Google Home, or watching a TV show recommended by Netflix—AI is everywhere.
AI Business shares that by 2020, it’s expected that 75% of commercial enterprise apps will use artificial intelligence. Additionally, experts are predicting a 4,300% increase in annual data production by 2020.
IBM Fellow, vice president and chief technology officer at IBM Watson Rob High emphasizes, “We’re only 7 years into the current era of AI computing. We’re likely to see another several decades of improvement.”
2020 is not that far away, and yet AI is still poorly understood by the majority of the population. Start getting informed on AI today by signing up for our newsletter below.
Google Makes Strides Against AI Biases with Contest
In an effort to remove bias in artificial intelligence and machine learning, Google created an open challenge, the Inclusive Images Competition. Teams were challenged to build algorithms that recognize “more diverse people and customs,” reports Futurism.
For example, most machines know that a woman in a white dress is considered a “bride.” However, they don’t label Indian women in wedding saris equally.
To achieve this distinction, teams had to creatively train their algorithms with labeled data that included more culturally inclusive images.
These algorithms were then put to the test of labeling images sent in from volunteers around the world. The top five performing teams would receive $5,000 in prize money.
At the conclusion of the contest, none of the competing teams was able to create a perfectly unbiased algorithm. But, one of them was able to identify Indian brides. Nonetheless, this represents an important step forward in designing ethical artificial intelligence.