The rise of the marijuana industry in the United States is upon us, and existing cannabis intoxication detection methods such as urine, blood, or saliva tests were not designed for cannabis and have significant limitations. Simply testing positive for the THC metabolite is not an indicator of impairment. However, a study published in the Drug and Alcohol Dependence, led by Steven's Institute of Technology assistant professor, Sang Won Bae reveals how smartphone technology may help bridge the gap.

With the use of the co-developed smartphone application, machine-learning models were used by Bae in research for detecting binge drinking. In addition, according to a press release, the algorithm could help law enforcement, employers and health professionals predict if a person is currently experiencing 'cannabis intoxication’, as well.

Is it truly as accurate as it is perceived? This testing method raises a conversation amongst the cannabis community, as well as, your average adult-use consumers and medical patients.

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