Software engineer Kesha Williams is the founder and creator of S.A.M.
Everyone loves the movies. Hollywood has a great way of triggering our imagination to think that what is being viewed on the screen can happen in reality. While there are many movies that depict real life situations, with a few science fiction elements added, how often do you actually consider they can come to life?
Meet Kesha Williams, a software engineer at southern fast-food king Chick-fil-A and a recipient of the Ada Lovelace Awards, a yearly event celebrating women in the field of technology. Williams was nominated in the Computer Engineer category for her groundbreaking work in building S.A.M., short for Suspicious Activity Monitor, a futuristic policing technology predicting the likelihood of crime. If you are thinking that this concept sounds like something straight out of a movie, you’re thinking correctly.
“I love science fiction and Minority Report is one of my favorite movies,” Williams said. “In that movie, they have this concept of pre-crime and they used psychic technology, so I started thinking what technology do we have today that can make predictions?”
Mr. Mission Impossible, Tom Cruise, starred in the 2002 blockbuster hit based on a short story by Philip K. Dick, telling the futuristic tale of Washington, D.C.’s Precrime police stopping murderers before they commit the act, reducing the murder rate to zero. Williams’s love for sci-fi and adoration of learning new things is how S.A.M. was born.
How exactly does S.A.M. work?
Anyone can have a conversation with S.A.M. using Twitter. While walking down the street, if they saw someone that may be engaging in suspicious activity, the user can take a picture and send it as a tweet. S.A.M then pulls the photo from the tweet and sends it through computer vision technology. Finally, the crime fighter will make a crime prediction and send it back to the user, telling them to either “run for their life!” or “there is no evidence of a crime about to occur.”
What is the key differentiator between Minority Report and S.A.M? During the creative processes stage, Williams said she wanted to shake things up a bit and had an “Ah Ha!” moment. “There are many attributes like age, gender and day of the week that all go into making a crime prediction but I intentionally excluded race because I didn’t want S.A.M. to be accused of using racial profiling,” Williams said. “When I did that, I thought that we could use this technology to remove human bias.”
The mother of three proves that you are never too experienced to learn new and exciting things. That brief pause in thought has allowed Williams to travel the world speaking on the findings of machine learning and how it can remove human biases from policing, hopefully making racial profiling a thing of the past.
The next phase of S.A.M.
The IT vet self-funded the development of S.A.M. With this type of technology that could change the world, many would think investors are flooding her inbox and knocking on the door to be a part of this project, however, Williams said that just hasn’t happened yet. “Really for me, S.A.M. was just a learning opportunity,” Williams said. “Because of what I’d learned, I really just wanted to share the knowledge with others.”
She may not have any partners now, but in the future, Williams will be enhancing the program, adding numerous attributes to help S.A.M. catch criminals. “I would like to add facial recognition. Since he already has computer vision, I would like for him to be able to identify the person in the photo,” Williams said. She also would like to link the system to police department data, pulling criminal backgrounds of those that S.A.M catches.
When asked which particular crime S.A.M. would be the most useful for, Williams says the technology is beneficial to them all with the use of predictive policing, the use of mathematical, predictive and analytical techniques in law enforcement to identify potential criminal activity. “Many people don’t realize that predictive policing is used today,” Williams mentioned. “It is used in courthouses. For example, a judge can use machine learning to predict if a person will be a repeat offender and that helps them make a ruling.” Technology like S.A.M. is already used by the Department of Homeland Security, mostly used in airports to determine if passengers have criminal intentions.
More about Williams
Besides being a full-time innovator, Williams is very passionate about building diversity in the field of tech. She writes about it on her blog called ColorsofStem.org. The blog is a platform to highlight women in STEM (Science, Technology, Engineering, and Mathematics) and just showing positive role models to the younger generation.
With a budding career in Information Technology and raising three future computer science majors to follow in her footsteps, Williams has no intentions of stopping now. She said learning new things is just the way she is wired. “I feel like S.A.M. is my introduction to machine learning. I really feel like artificial intelligence and machine learning is going to be the next wave of informative technology,” she said. “I definitely want to expand and grow in A.I. and deep learning. Our reliance on these technologies is going to continue to grow so for me, I just want to continue learning.”
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