How long did I sleep? How many steps did I take? How many calories did I eat? These questions were the mainstay of the Quantified Self movement. While getting the data on your life was alluring — even addictive — it rarely revealed fresh insights. A new category, Qualified Self, built upon on AI which can analyse qualitative information, may take its place.
The demise of Quantified Self
The Quantified Self movement aimed to provide “self-knowledge through self-tracking with technology.” It boiled life down into questions of quantity. Mostly, the data would confirm to us what we already knew — I slept badly, I ate too much, I didn’t move enough today. At its best, Quantified Self was successful at habit formation, by gamifying life with neat categories.
But based on its own definition, the Quantified Self movement failed. It tracked us, but it didn’t reveal us. The movement hit its peak in 2013 and then crashed — at least according to its Google searches.
The failing of the Quantified Self movement was that it fetishized data and missed out the nuances of human experience. The work to understand ourselves is much more of a qualitative task.
Enter the idea of ‘Qualified Self’. Where Quantified Self was concerned with counting surface data, Qualified Self digs deeper: it aims to understand the quality of human experience. It asks, in what way? How? And even — why?
Answering these questions requires analysing richer and often slippery data-sets: language, texts, images, experiences, information that resists categorisation and requires subjective interpretation.
So, when it comes to self-knowledge, our assistance has traditionally been purely human — therapists, coaches, priests, good listeners and sharp questioners. Meanwhile, the best tool available for self-knowledge has long been a journal.
But advances in AI, machine learning and Natural Language Processing are enabling qualitative data to be interpreted by computers, creating the potential for Qualified Self digital tools for self-knowledge.
Qualified Self, as an emergent application category, could be defined as “Self-knowledge using rich self information, assisted by AI.”
Take-home example: Scribe
Currently in pre-launch beta, Scribe is a Mac OS journaling application which provides a good example of the emergent category of Qualified Self. The app promises to be “like therapy, but without the cost or commitment.”
Scribe uses a machine learning algorithm to analyse users’ journal entries and to provide feedback. Today, Scribe’s feedback is limited to revealing the potential emotions present in the entries, based on the AI’s interpretation.
Scribe reveals these insights once a minimum of 200 words is written. The enjoyably clean writing space and the reward of feedback after entry completion will benefit those who are new to journaling or struggle to keep up the habit.
The instant feedback Scribe offers is exciting because of the slow nature of journaling, where the ultimate rewards are very long-term, which can make motivation challenging.
Adding human insights
Scribe is an exciting signal of how AI can assist in self–knowledge in the future. But without context or further interpretation, speculating emotions from text will rarely be valuable — based on the current UX, the real benefit is encouraging getting people to do the work of journaling.
My prediction is that it will be the creators of such apps which draw on existing insights into the human psyche who will win in Qualified Self.
Armed with humanities-based insights, Qualified Self can create a lot more value for the user. For example, the AI could spot ethical dilemmas and explore ethical frameworks, offer well-being tips from positive psychology, explore developments in character … or even reveal interpretations of dreams using psychotherapy models.
Moreover, as the players in this space build on shared platform AI technology, it will be how they build in psychological and philosophical models that will provide the main way to differentiate.
The future of Qualified Self
Perhaps one day Alexa will have a coaching function. In the meantime, Qualified Self text-based applications will emerge in all the contexts surrounding personal growth: therapeutic, life coaching, health, fitness, dating, professional and education. Successful apps will help us make this process of self-discovery rewarding, habitual and joyful.
At its best, Qualified Self will combine technological advances with existing insights into the human psyche, because for now, humans will know humans better than machines do. If we don’t fall into the trap of reducing human development and self-knowledge to data alone, Qualified Self has an intriguing future.
Thanks for reading! I’m an innovation strategist & facilitator based in Berlin. I write on putting people before technology, and making space for deep work. You can find me on Linkedin.