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AI Contextual Awareness Engine

Redefining Serendipity With Location Data

The ironic thing about predictions for the future is talking about them in past tense. On the same note contextual predictions with rapidly changing environments can be interesting. I will jump back less than a year to Foursquare and their prediction of the future.

This was a small mention before going into vastly generic statements about the future 10 years from now. However it is this small mentioned that made me interested. What is Pilgrim SDK?

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Foursquare Pilgrim SDK

I will mention the three selling points with a few mentions of product features. After this I will spend three paragraph reflecting on these.

  1. Contextually-aware serendipity. Magical moments through venue-detection. In short: Foursquare knows where you have been through its collection of data and can therefore sell you better. They have data of 105 million places available across 238 countries and territories .
  2. Personalise outreach with behaviour-based audience profiles. Pairing location tech with transaction history to create profiles of people’s (‘users’) behaviour.
  3. Know your customer based on real-world visits. There is an argued increased customer ‘lifecycle’ due to granularity of insight provided by the most accurate place and venue detection. This apparently includes flagging repeat locations.

Is it problematic to be repeat locations with home and work detection? I sincerely doubt that Foursquare tells their users that they are tracking them so actively. This does however seem like common practice. Late last year a researcher found that Google tracked your location history and understood your home and daily activities despite turning off location history.

Then again there’s so many ways to track. In-home devices, wearables, smart TV, and email help create an accurate image of you. Serendipity can mean an unplanned fortunate discovery or by chance in a happy beneficial way. If the translation is data-driven behaviour tracking and slight influence to change your or in more layman terms the way you behave — we can seriously question this phrasing.

After talking to several technology firms and now most company delivering a there seems to be a trend talk of users. We might question whether this allows us to distance ourselves further from other people part of our society. or is tracking how people move or what they do. When we call it or is it possible we loose touch with the people we are working with as opposed to to?

These may seem like hippie notions, yet language is certainly part of the way we communicate and it shapes our actions. Programming language certainly does too. We have (or about) psychographic information (personality, values, opinions, attitudes, interests, and lifestyles) and combine it with location as well as optimise for certain goals.

Optimising could be done through the field of AI with techniques such as machine learning as well as reinforcement learning. The AI contextual awareness engine gives a compelling reason to pause and think who sets these goals and which type of responsible use this requires.

We have to think more closely on how the field of contextual AI will influence interaction in society — or how in many ways it already is.

This is day 14 of my project #500daysofAI.

What is #500daysofAI?

I am challenging myself to write and think about the topic of artificial intelligence for the next 500 days with the #500daysofAI.

This is inspired by the film 500 Days of Summer where the main character tries to figure out where a love affair went sour, and in doing so, rediscovers his true passions in life.

PS: Foursquare please correct me if there is anything wrong with what I have written. I do find this to be an interesting topic.

Written by

AI Policy and Ethics at Student at University of Copenhagen MSc in Social Data Science. All views are my own.

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