Recently the founders of Metaphysic used AI to create a live performance by Simon Cowell on America’s Got Talent signing. They used a special camera, a body double that has a great voice, and an AI model that was trained by examining footage of Cowell.
Although in this video, you can tell it isn’t quite right and that isn’t Cowell, it was convincing enough to be a semi-finalist in AGT. Their DeepFake Tom Cruise, on the other hand, is more convincing. If you look closely, you can see it probably isn’t Tom himself, but at first glance, many fans would be fooled.
Metaphysic is using synthetic media to create these clips. They combine real-world objects with digital ones created with artificial intelligence. For the Tom Cruise videos, they spent 3 months analyzing a variety of clips of Tom Cruise from movies, interviews, and any other coverage. The videos are created with a body double with the AI-generated video of his face.
For entertainment purposes, this can open up some new opportunities, but it adds many ethical questions, not just in entertainment but in business, politics, the legal system, and the world at large. As AI becomes more developed, the images will be clearer and less distinguishable from real ones, and there are significant implications. Right now the technology is quite expensive to use and generate these types of images, but this will change as well.
To see the entire article on Metaphysic and a discussion of synthetic media, see this article by Bernard Marr.
In a recent study at MIT, researchers evaluated facial analysis programs from major technology companies. The research shows major error rates when asked to evaluate women and people of color.
The facial recognition software algorithms were built using neural networks, which look for patterns in a large set of training data. One technology firm boasts 97 percent accuracy in face-recognition software. However, the neural network was trained using a dataset that was 77 % male and 83% white.
MIT researchers evaluated a similar program and used a dataset that included a wider range of people based on gender and skin tones. In the three commercial software systems, error rates of 20.8, 34.5, and 34.7 percent were found for darker-skinned women. This is compared to the 3 percent claimed by one of the system developers.
For more information on these findings, go to: MIT article
At the Consumer Electronics Show earlier this year, John Deere showcased how it is using Artificial Intelligence in its products. A large display of agricultural equipment is not what many attendees expect to find at the consumer electronics show, but a John Deere Sprayer was displayed prominently among the drones, games and other gadgets.
The algorithm made me do it shows one of the primary reasons explainable artificial intelligence will be needed in the future. Many AI solutions seem to be a black box which few, if any, individuals can explain the particular output.
This Harvard Business Review article highlights why the black box approach to AI in the future won’t be feasible. The author notes that the “The algorithm told me to do it” defense won’t likely stand up in court.
A recent trend in social media is the use of FaceApp. Upload your photo and it will return an image of how you would look in the future. You may also use the app to change your appearance in a variety of manners. Although it appears to be a fun use of Artificial intelligence, are you also giving them permission to use your photo?
From FaceApp’s Terms and Conditions: ” You grant FaceApp consent to use the User Content, regardless of whether it includes an individual’s name, likeness, voice or persona, sufficient to indicate the individual’s identity. By using the Services, you agree that the User Content may be used for commercial purposes. “
According to this, they can use your photo as they like — including selling it.
Harvard Business Review named the data scientist the sexiest job of the 21st century. This job requires significant computing and statistical skills.
With the rise of analytics and artificial intelligence, these skills are needed, but even more critical are individuals that have excellent business acumen.
These individuals can fill the role of translator. Not in the traditional language sense, but translate business requirements for the technical individuals.
” translators play a critical role in bridging the technical expertise of data engineers and data scientists with the operational expertise of marketing, supply chain, manufacturing, risk, and other frontline managers. In their role, translators help ensure that the deep insights generated through sophisticated analytics translate into impact at scale in an organization. “