Curating cannabis with your personal data
The legalization of an industry that has been operating in the dark for decades, in this case cannabis, means ample newfound opportunity for government and corporate-funded collaboration, development and research. In recent years, Artificial Intelligence and Machine Learning have exploded onto the market, whether through products like Google Home and Amazon Alexa, or as means for targeted advertising. The bridging of personalization technology to cannabis would not only push the boundaries of access to alternative medicine, but also promise a boutique experience much like Uber and food-delivery services.
Currently, the data that corporations collect through machine learned artificial intelligence is primarily used to better understand its consumers, whether for their own purposes or to sell to other companies. The aim is to drive revenue through targeted advertising, which is based on an individual’s derived profile. Most often, the data stays within corporate powers; the user is unaware of how their data is analyzed and used.
In this context, there would be an important shift: the data would become the product that users are purchasing. Imagine, in relations to the cannabis industry, if customers had access to an app that uses an algorithm to recommend the most suitable strain based on their needs calculated from their personal data. In this personalization model, the company directly generates revenue from the consumer by providing a service that involves the analysis of the consumer’s data, which is then given back to the consumer. In the previous model of ad targeting, revenue is generated in layers by throwing ads at an individual that align with their profile in hopes that they are persuaded enough to then act on their consumption.
In a 2018 The Guardian article by Arwa Mahdawi, she explains that Spotify helps marketers target consumers with adverts tailored to the mood they’re in through data analytics of “the sort of music you’re listening to, coupled with where and when you’re listening to it, along with third-party data that might be available.” Expanding on this notion, it is likely that data analytics will advance to provide even more accurate examination of one’s mood, insofar as it can even understand the complexities of one’s health status, chemical balances and even predict how an individual will likely be feeling in the near future. We have already been involuntarily inundated with data collecting apps, such as Apple’s default Health, Maps and Calendar apps. A decade from now, the amount of data that individuals will have generated, in combination with technological advancement, will no doubt pave the way for precise diagnosis of one’s emotional and physical conditions. A combination of data from some basic apps alone — such as an exercise tracking app, music app and Internet browsing app — provide copious information about an individual’s physical and emotional states.
A quick example: I use a menstrual cycle tracking app that accurately predicts — to the day — when my menstruation will begin and end. Paired with a cannabis app, this could be used to prescribe a strain high in pain relief for the dates of my expected menstruation. Or, to take it one step further, it could also mine my calendar to know that I attend yoga classes, and thus suggest that I go to a studio that offers weed yoga sessions. In a broader sense, it could predict spikes in my stress and depression levels based on upcoming school exam dates, logged in my calendar, and the music I have been listening to.
In combination with enhanced personalization, instant-deliverable technology would allow the product to be received just minutes after ordering. This function is crucial, as it keeps prescriptions relevant to your specific needs at that specific time. The service would commission drones to complete a delivery (much like Uber), picking up the goods from the nearest warehouse, privatized distributor, or government-sanctioned pharmacy. A decade ago, same day delivery would have been deemed outrageous, yet Amazon Prime has proved that entirely wrong. A decade from now, deliverables are bound to reach even higher speeds at higher volume.
Though data collection summons many ethical concerns regarding privacy, it also provides extensive opportunity to improve our day-to-day lives. If technology can determine that I am sad because Spotify shows that I’ve been listening to Kanye’s 808s & Heartbreak on repeat and Maps reveals that I’m frequenting the cinema for tearjerkers, then we are only a stone’s throw away from technology that can evaluate our most complex medical histories and use it in conjunction with our recreational habits to better prescribe alternative medicines like cannabis. In an ever-growing effervescent digital world, it seems likely that society will continue to latch onto the use of cannabis products — whether as a form of escapism or to counteract the effects of a tirelessly on-the-go world.
