There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.

Kimberly Krawczyk says she would do anything to keep her students safe. But one of the unconventional responses the local Broward County school district has said could stop another tragedy has left her deeply unnerved: an experimental artificial-intelligence system that would surveil her students closer than ever before. The South Florida school system, one of the largest in the country, said last month it would install a camera-software system called Avigilon that would allow security officials to track students based on their appearance: With one click, a guard could pull up video of everywhere else a student has been recorded on campus. The 145-camera system, which administrators said will be installed around the perimeters of the schools deemed "at highest risk," will also automatically alert a school-monitoring officer when it senses events "that seem out of the ordinary" and people "in places they are not supposed to be." The supercharged surveillance network has raised major questions for some students, parents and teachers, like Krawczyk, who voiced concerns about its accuracy, invasiveness and effectiveness. Her biggest doubt: that the technology could ever understand a school campus like a human can.

For all their stunning frequency, school shootings remain a confounding horror. Not only is there little consensus on how to stop them--with suggestions ranging from restricting gun access to arming teachers--but there's even less certainty about why a student would open fire on his classmates. Now, some scientists are starting to explore if artificial intelligence (AI) could help find answers. The idea is that algorithms might be able to better analyze data related to school shootings, and perhaps even identify patterns in student language or behavior that could foreshadow school violence. The research is still in its early stages, and the prospect of using machines to predict who might become a school shooter raises privacy issues and other ethical questions associated with any kind of profiling, particularly since the process would involve children.

Scientists have developed an artificial intelligence system that can help predict which students are at higher risk of perpetrating school violence. The researchers found that machine learning – the science of getting computers to learn over time without human intervention – is as accurate as a team of child and adolescent psychiatrists, including a forensic psychiatrist, in determining risk for school violence. "Previous violent behaviour, impulsivity, school problems and negative attitudes were correlated with risk to others," said Drew Barzman, a child forensic psychiatrist at Cincinnati Children's Hospital Medical Center in the US. "Our risk assessments were focused on predicting any type of physical aggression at school. We did not gather outcome data to assess whether machine learning could actually help prevent school violence. That is our next goal," said Barzman, lead author of the study published in the journal Psychiatric Quarterly.

A pilot study indicates that artificial intelligence may be useful in predicting which students are at higher risk of perpetrating school violence. The researchers found that machine learning - the science of getting computers to learn over time without human intervention - is as accurate as a team of child and adolescent psychiatrists, including a forensic psychiatrist, in determining risk for school violence. "Previous violent behavior, impulsivity, school problems and negative attitudes were correlated with risk to others," says Drew Barzman, MD, a child forensic psychiatrist at Cincinnati Children's Hospital Medical Center and lead author of the study. "Our risk assessments were focused on predicting any type of physical aggression at school. We did not gather outcome data to assess whether machine learning could actually help prevent school violence. That is our next goal."

The researchers found that machine learning -- the science of getting computers to learn over time without human intervention -- is as accurate as a team of child and adolescent psychiatrists, including a forensic psychiatrist, in determining risk for school violence. "Previous violent behavior, impulsivity, school problems and negative attitudes were correlated with risk to others," says Drew Barzman, MD, a child forensic psychiatrist at Cincinnati Children's Hospital Medical Center and lead author of the study. "Our risk assessments were focused on predicting any type of physical aggression at school. We did not gather outcome data to assess whether machine learning could actually help prevent school violence. That is our next goal."