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. “
To develop a new Artificial Intelligence model, it needs to be trained. This is done by processing a large amount of data several times until the model works.
With AI models becoming more complex, larger datasets are required to fully operationalize the model. This is taking significant amounts of computing power, and thus, electricity.
In a study at the University of Massachusetts, researchers found “that the process can emit more than 626,000 pounds of carbon dioxide equivalent—nearly five times the lifetime emissions of the average American car (and that includes manufacture of the car itself). “
Similar issues have been raised with Blockchain mining, in particular Bitcoin.