COVID-19, behavior knowledge and Internet of Behaviors (IoB)
April 23, 2020 § 1 Comment
Gartner has included the concept of Internet of Behavior (IoB) in their Top 20 Strategic Predictions for 2020 and beyond (10/2019). They explain the reasons to this choice:
“The Internet of Behavior (IoB) will be used to link a person digitally to their actions.”
“IoB will also be used to encourage or discourage a particular set of behaviors”
In other words, IoB builds a digital connection to the actions of people, which allows accurate targeting and offering information and services to guide their behaviors. The relevance of this to epidemiological considerations is self-evident and here I shortly consider some of the potentials of IoB for fighting the virus.
When the aim is global and secure monitoring of behaviors, something like IoB is needed to make data collection and use compatible everywhere. Current tools and apps make up a digital Babel. I want to make clear here that this must and can be accomplished in IoB without revealing the identities of behaving people. From the perspective of an ideal IoB, a person taking the vaccination against COVID-19 (in future) is no different from another person with the same behavior (vaccination) in another part of the world. They only share the behaviors and it is a matter of interest how this information is then used and combined with other behavior information, and what these people allow, for medical follow-up purposes, for example.
To put it simply, detection of a behavior, can be accomplished either automatically by any of the current and near future personal gadgets and smart sensors or by allowing people express their behaviors, mental or physical and of any complexity. Clearly, the latter has a major potential for individuals, communities and service providers.
Why would people use IoB? It is meant to secure timely, relevant and accurate communication, offerings and services, better than any AI/ML based system can achieve when it comes to personal and situational needs. In case of a pandemium or other global, national or local threats such a situational intelligence and 100% relevance in communication matter.
I’m not an epidemiologist, far from that, so this is a look of a behavioral scientist.
Coincidentally, the original sources to IoB are my two blogs from 2012 and recently I included IoB in my book “On the Edge of Human technology – An Essay”. I had a vision we could target any ongoing, intended, imagined or planned behavior on earth (like we do with IoT, targeting systems, gadgets and devices) and approach people exactly at the right time and with relevant information and services, when certain behavior occurs – and to do this without necessarily knowing who these people are. The underlying idea was and is that often it is sufficient and beneficial to know the occurring behavior, not the identity of the behaving person. Being a psychologist, it is no surprise I used the form behaviors instead of behavior, which Gartner used.
Fighting the CORONA-19 virus, societies try to follow and predict individual and social behaviors and target citizens with relevant information, instructions and even orders.
Lockdown of behaviors
The global lockdown is meant to control human and especially social behaviors. Because there is no means to know exactly where and how these behaviors occur and will occur, the responsible organizations and specialists provide general, non-specific comments, instructions, guidance and orders. Their hope is that people will follow them. The challenge is to reach people at the right time and with the right kind of information and services.
When epidemiologists offer their specialist knowledge and politicians and journalists add their interpretations to it, media becomes crowded with stories, often conflicting, on behaviors to avoid and instructions to follow: no partying at sport bars, no participating at weddings or funerals, cancelled mass gatherings, use/no use of masks, or no crowding shops. Fresh news emerge about “super-spreaders” who have been known to e.g. share a room with others, going to a certain restaurant, to a wedding, or partying. Large-scale and accurate, real-time maps of occurring or emerging human behaviors do not exist.
The list of forbidden and restricted human behaviors is long but as of yet, there is no exact method to monitor them automatically. The uses of AI and face recognition for example, are too crude and difficult to adapt quickly to the new situation. It would be beneficial if we could get the behavior data directly from individuals, which would allow following them and targeting their virus-related behaviors early, with guidance, information and services to support the virus fight. I want to be clear here: by “following” I mean following behaviors, not individuals – unless they so want or allow it to happen.
It is not known what exactly are the most dangerous specific behaviors: they can be, for example, personal acts or styles, any forms of social and bodily interaction in sports and entertainment, or it can be about the combination of these with physical spaces and their conditions, like ventilation, hygiene facilities and practices where close contacts happen. Unfortunately, tracing such behaviors post-hoc or tracking them in real time is very difficult or impossible. For example, why isn’t there a service in restrooms that when a person tries to leave it without washing hands, it would have a way to remind of it? This would require behavior coding like in IoB: someone can visit a restroom and use the mirror only J
Schools have been closed in many countries, but now they are slowly opening and a new knowledge need emerges there, too: students and teachers are instructed to behave in certain cautious ways but it is difficult to collect data on what actually happens and what consequences different behaviors have. Specific tools are needed and IoB or similar solutions could help in this.
A flood of news mentions certain individuals and their behaviors (super-spreading) that boost the spread of the virus. For example, Dr. Hendrick Streeck told The Guardian that where there is dancing and singing, the virus spreads fast. However, the burning question remains “What exactly are the virus spreading behaviors”. There is more to our behaviors than dance and singing.
Better and informative behavior data is accumulating fast and under global scrutiny. When the most ‘dangerous’ behaviors are known, people can be targeted and guided accordingly. In many, if not in most cases, this could be done, based on their behaviors, but without knowing who these people are.
As expected, apps with standard technologies like GPS and Bluetooth have been quickly introduced to monitor the movements and whereabouts of infected or potentially infected people. Knowing where they move or when they are in the vicinity of others is hoped to help prevent contamination and spreading of the virus. Anonymity and voluntary use of the apps and tools are emphasized. People have had the bitter lessons on how their personal data is used by network giants and their networked partners and are getting now eager to protect their privacy even and especially during a crisis like this. Indeed, there are reasonable worries concerning such detailed identity data if it can be used for other purposes, for example, by insurance companies, financial services, or by any other sectors benefitting from intruding people’s private life.
Some technologists doubt the use of their location (GPS) data for tracing purposes while others have seen problems in interpreting Bluetooth –based data. No doubt, these problems will be solved, and the tools will be useful during the post-virus recovery and follow-up time and then of course, for the next crisis to come. https://www.bbc.com/news/technology-52353720.
What could be relevant behavior knowledge?
Behavior knowledge is more than what we directly observe of a person. For a psychologist, it is natural to include planning, emotional experiences, interpretations and intentions, for example, under the term ‘behavior’. IoB is meant to cover and ‘code’ any of these human phenomena. Much, if not most of our behavior is internal and relative-to-others in nature. We can know the exact location of a person, her movement patterns, or participation in gatherings but still fail to understand her or know the intentions and motivations behind the observed behavior pattern. From the outset, people can behave in similar-looking ways but for completely different reasons.
Present digital technologies monitor simple observable behaviors, which has its undeniable value in entertainment, sports, health and life-coaching apps. Interestingly, Spotify can be considered as a primitive form of IoB since it lets people express their wishes and to be rewarded by relevant music when they so want – the behavioral loop is inbuilt in it.. Much more could be accomplished with IoB there as well.
With mature IoB it becomes possible to detect any behavior, external and internal alike, that can be coded or expressed so that when it occurs, the person – her media environment – can be accessed accordingly. As human beings, we are the best experts of our minds, of our experiences, intentions, value priorities, and mental states, better than any AI/ML system. Simple and effective means to indicate this mental information has huge human and social potential and invites to accessing each other at the right time and with relevant messaging and services. By ‘accessing’ I mean the possibility to approach a person via any of her own app or tool or by directing information to her visual/audio environment.
An exceptional form of knowledge in preventing the spread of the virus would be reliable intention knowledge or knowledge of a person preparing to do something that increases the risk of infecting someone or to be infected. In web and mobile apps this can by arranged by asking the person using the app but this is a cumbersome maneuver and does not ‘live’ with acute life situations. More dynamic apps are needed to make IoB ‘conversation’ seamless and even fun.
Many would argue that people are unreliable in expressing their intention data. However there are masses of human intentions that predict certain behaviors with a very high probability, and it would be useful to have this knowledge. It’s no rocket science that a person knows when he’s going to eat something, take a medicine, visit a friend, before he is there, sometimes days, hour, minutes before it. From the virus perspective, it would be extremely valuable to have this pre-knowledge and to inform him or other people from that future or near-future behavior. In case of hospitals and health care services in general, there is much more to it – this knowledge can be critical if we had it. The benefits scale up with masses. How to get access to such data and would it be safe?
Why is behavior data linked with the identity?
Prominent public figures have expressed their fears that the pressure to track people can become a permanent social practice with dire social and political consequences. Their worry concerns technological solutions, where identity data is intimately linked with other data of the individual, as is the general practice today. However, this need not be so.
Most digital apps and tools that use our behavior data, like when messaging, traveling, visiting places, using services and exercising, indeed record both the person’s behavior and her/his identity and uses this for various purposes. Historically it was a dominant social practice in public, financial and health care services to trust our identity data to these services. This is how behavior data became de facto behavior+identity data and most analysis tools use both of these components to target the campaigns, services and any lures of life.
Interestingly, still some 50 years ago, there was not much public worry about id data, but then the net changed everything. Anonymity is now added in case the users especially want it, but it is far from a standard feature of the services we use and most of us don’t have a faintest idea where our identity data is stored, shared and how it is directly or indirectly used. GDPR helps but it is only a superficial cure to this paradigmatic trend.
Getting relevant behavior data – with IoB
Originally, when developing the IoB concept, I imagined the following:
“What if we could know, when, at a specific moment of time, certain human behavior occurs somewhere on the globe, and we could be in touch with all these people, from single individuals to millions, behaving like that, but without knowing who they are or where they are unless they voluntarily disclose their private data?”
How could we get that data and what could we do with this huge global and local pool of behavior knowledge? Internet of Behaviors is meant to support services, which systematically record, code and use behavior data, which is not automatically connected with the id of the behaving person.
In the case of COVID-19, the behavior data collected via an IoB app would allow monitoring single individual or communal behaviors occurring right now in masses. This can then be supplemented with relevant context data like geographic, organizational, process, community, medical, economic, or any other background information that allows mapping the ongoing behaviors on whatever is the context or domain of the behavior.
As a simple acute example, a pharmacy could offer its own IoB app to its customers and let them indicate (web, mp) when they plan to visit or are on their way to the store, so that the store can be prepared, especially if crowding is expected or a Corona patient’s family member is coming to fetch the medicine. There are various ways this information can be used at the pharmacy but also within a broader local context – without revealing the identity of the ‘behaving persons’. Communication is two-way which allows the pharmacy to send information to the person(s) but again without necessarily knowing who he/she is unless they have made an arrangement in the IoB to share private information. Then of course, the IoB approach has a multitude of uses elsewhere and scalable.
IoB can provide predictive information – about any intentions and plans, related to the situation at hand, like COVID-related behaviors. When a large enough pool or crowd of people use an IoB app, it becomes a tool, for accurate forecasting, This makes it different from any app aiming at following movements, tracing people, detecting locations and occurring closeness of people. Together, however, these approaches can make up a very powerful and situationally intelligent service. IoB can be integrated in these recently published tracing apps.
In practice, with the IoB app, the user could easily indicate or select from a set of alternative behavior codes or have a link to any personal QS gadget like Oura ring, or use QR devices, or otherwise indicate the ongoing or her/his intended behavior and so on. It is a matter of innovation to figure out the most feasible, seamless, automatic or semi-automatic ways to let people indicate their behavior in IoB, with a push of a button or why not with spoken comments.
IoB has exceptional power if it is developed in coordinated and standardized manner so that it makes coded behavior data accessible globally and makes it usable for any possible purposes. Apps can be designed for limited use like the pharmacy case above, but already there, the data structures should be designed so that they allow significant scaling up. Originally I imaging that IoB could use IPv6, with a pool of dynamic addresses reserved for certain behavior classes and which various service providers could then use and distribute. This is not mandatory and other forms of behavior coding is possible, for example so that it makes possible a private, even dynamic definition of behavior codes between the client and the IoB service provider.
Some aspects of design
Basic IoB features can be easily integrated or built into current web and mobile services and tools. When anonymity is required, it can be added. However, IoB could be built on its own architecture, supporting environment and protocols, just like IoT. I am tempted to imagine that because of its versatility and the way it can touch practically all aspects of human and social life, an IoB device could find its own independent place as a personal IoB-gadget – not part of a smart phone – or as an integrated part of any smart devices or ubiquitous ict. These visions are exciting.
I have given a superficial description of the IoB as I see only some of its potential value in fighting a global pandemia or other global threat . This is by no means a product or service description, but I hope it inspires design thinking for developing IoB in practice.
Gartner (2019) Top 20 Strategic Predictions for 2020 and Beyond.
Nyman, G. (2012) Internet of Behaviors.
Nyman, G. (2012) The Psychology behind the Internet of Behaviors.
Nyman, G. (2020) Behavior data in the net. In: “On the Edge of Human technology – An Essay” Amazon.