Artificial intelligence, robotics, and nano-devices, among other rapidly expanding technologies have an overwhelming potential to shape many aspects of our not too distance future, not least our medical care.

With somewhat ease, we can now visualize a future with automated referrals, prescribing, monitoring and discharge – streamlining and synchronizing the care we receive.

However, it will be critical that such advances do not undermine what behavioural science and psychology have cemented over the last half century: that, contrary to standard economic theories, humans are not always rational. How we make decisions, such as whether to take a medicine, are complex and multi-factorial.

Consultations can often be key to ensure the optimal decision is reached. However, with automated services such as robotic drug dispensing, such human-human interactions will be lost.

Devices do not always have to be ‘unhuman’ though; many have been designed to be behaviourally smart. Such devices consider the irrational facets and individual complexities in human behaviour to improve outcomes and help people make better decisions for healthier, happier lives.

With the expanding accessibility of big data there is also a new opportunity to take advantage of, as quantitative behavioural insights and analysis can facilitate increasingly tailored and personalized support through medical devices.

Incorporating an understanding of human behaviour into artificial intelligence and other innovative medical devices will be vital in future healthcare, but done correctly could offer great potential to improve health outcomes.

How we perceive the implications of an illness and potential treatments in the present compared to the future can shape our attitudes towards treatments and thus influence adherence and outcomes.

We have a tendency to choose small short-term gains over long-term larger ones, which is described as temporal discounting. The value of an item today appears to be worth more than in the future.

This tendency to make choices which bias the present, often to our long-term detriment, is particularly prominent in smokers1 and can also be applied to medical adherence. Discounting in the value of future health risks, has been found to be correlated with adherence and treatment outcomes in both diabetes2,3 and multiple sclerosis.4,5

One potential reason why we favour the present could be linked to future-self continuity, how we perceive ourselves now, in comparison to ourselves in the future. This also links to illness perception. If the person does not feel ill, the benefit is not obvious, so it is difficult for patients to even discount.

In experiments, when participants are asked to assess how similar they perceived themselves to their future self, using the sets of circles (see below) and then undertake a temporal discounting task to see how likely they were to choose delayed monetary rewards (e.g. £15 today or £50 in three months), future-self similarity (assessed by the circle task) correlate with their likelihood of choosing delayed reward. The more similar people perceive themselves as more similar to their future self the more they save.7

When shown avatars of either in their current state or looking elderly as a retired version of themselves8 and asked questions such as: How much of your current income would you like to allocate for your retirement fund? Seeing the older avatar of themselves people increase the average percentage of their income they would choose to save.8

This has strong implications as it demonstrates that making a connection with our future self can help us make better, more forward-thinking plans, and patients make treatment choices more aligned with their long-term needs.

1. Bickel W, Odum A, Madden G. Impulsivity and cigarette smoking: Delay discounting in current, never, and ex-smokers. Psychopharmacology. 1999;146 (4): 447-454.

2. Lansing A, Stanger C, Crochiere R, et al. Delay Discounting and Parental Monitoring in Adolescents with Poorly Controlled Type 1 Diabetes. Journal of Behavioral Medicine. 2017

3. Lebeau G, Consoli M, Le Bouc R, et al. Delay Discounting of Gains and Losses, Glycemic Control and Therapeutic Adherence in Type 2 Diabetes. Behavioural Processes. 016;132: 42–48.

4. Bruce J, Bruce A, Catley D, et al. Being Kind to Your Future Self: Probability Discounting of Health Decision-Making. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine. 2016;50 (2): 297–309.

5. Jarmolowicz D, Reed D, Bruce A, et al. Using EP50 to Forecast Treatment Adherence in Individuals with Multiple Sclerosis. Behavioural Processes. 2016;132: 94–99.

6. Hershfield H, Wimmer G, Knutson B. Saving for the future self: Neural measures of future self-continuity predict temporal discounting. Soc Cogn Affect Neurosci. 2009;4 (1): 85-92.

7. Hershfield H, Garton M, Ballard K, et al. Don’t stop thinking about tomorrow: Individual differences in future self-continuity account for saving. Judgment and Decision Making. 2009;4(4): 280–286

8. Hershfield H, Goldstein D, Sharpe F, et al. Increasing Saving Behavior Through Age-Progressed Renderings of the Future Self. Journal of Marketing Research. 2011;48: S23–S37