Innovation for Safety

It is impossible to grasp all of the ways in which the pandemic is changing our way of life around the world. While most of the news coverage tracks the spread and death toll and the national/state government response to the virus, there is news on the efforts of local government, schools, business, and individuals to mobilize, survive and thrive in this new world.

Innovations in this time of disruption are inspired by our impulse to meet some basic human needs. We are searching for solutions; for our safety and security, our sense of belonging, agency (power), and expression (attention) to name a few. As with any innovation, some will be a flash in the pan, some will endure, evolve and be adapted into the fabric of our society. They are aimed at some basic need we have.

Safety and security

The need for safety and security is inescapable right now. The threat of infection and death, loss of loved ones, loss of our livelihood, and our entire way of life has us in it’s grip. While we stay at home, we search for new antidotes to our insecurity. This time of isolation has been a source of inspiration and reflection to some while it has led others to act out in protest, fearing the loss of livelihood more than death.

Following are a few examples of innovations inspired by our need for safety:


One development towards safety has been directed at an early warning system that is familiar to us all, the use of thermometers. By checking our temperature before we enter public locations and checking and sharing personal rises in temperature as they happen we may create a more effective safety net by identifying the pattern of infection.

Kinsa Health debuted it’s internet-connected thermometers eight years ago to track flu. The data the company is uploading for free to government and research scientists is helping pinpoint both where the next outbreak might occur and which communities are flattening the curve. They’re also proving that social distancing is working. – Here and Now – April 9, 2020

A Chinese startup “Rokid” is promoting COVID-19 detection glasses in U.S. : . Rokid’s T1 thermal glasses use an infrared sensor to detect the temperatures of up to 200 people within two minutes from up to three meters away. The devices carry a Qualcomm CPU, 12 megapixel camera and with hands free voice controls — to record live photos and videos.


How many tests do we need to feel safe? Labs around the world and in the US are exploring new methods for testing people suspected of infection. Some of these methods will evolve into new standards while some will prove inaccurate or impractical. Hospitals have adapted new ways of administering tests in an effort to reduce exposure by creating drive through testing. At the same time scientists are trying to lower barriers to testing. While supplies and personnel continue to be in too short supply, lacking a national effort at distribution, we must increase testing in order to feel safe to interact.

An average of 145,000 tests a day were carried out over the past week nationwide, or about a million a week, according to the COVID Tracking Project. Experts disagree about how many tests would be required to get a handle on the outbreak, but even the most conservative recommendations from former officials like Scott Gottlieb — head of the Food and Drug Administration until last year — call for at least doubling the current level of testing now and tripling it by the fall.

NBC News – April 17

While we continue to struggle with the necessary components of tests in the critical short run, researchers are moving forward with innovations that address the long term. Home tests are one of the approaches. While home tests run the risk of false positives due to contamination, there is an effort to improve them.

  • Saliva tests. A “Rutgers University scientist who oversaw the development of a saliva test to detect coronavirus said he believes this new way to collect patient samples could serve as a bridge to widespread national testing — modeled off the kits used by familiar commercial genealogical brands like and 23 and Me.” – ABC News – April 16, 2020
  • Antibody testing. These tests determine if a person has had the virus and carries antibodies that protect them. A team in the UK is working on a home antibody test kit. A team in California has an antibody test that is administered in the lab. They hope to “expand manufacturing of its new coronavirus antibody test for use by the public within two months.” The same story describes other antibody tests under development…

Only one [antibody] test, produced by the Research Triangle Park, N.C., company Cellex, is already approved and being rolled out for use in select groups. Two others are awaiting FDA approval. One is from Aytu Biosciences/Orient Gene Biotech; the other is ScanWell Health/INNOVITA.

Six other tests have been approved in the U.S., but they are only for research or surveillance purposes. Other tests are still in development.

Five antibody tests have been approved for use in China. In addition, one is approved in Singapore and one in Korea.

Mercury News – April 12, 2020

Tracers – Tracking

The success of re-opening our economy will depend on our ongoing success at containment. One essential component will be the ability to track person-person contact when an infected person is identified. Tracing these associations and contacting and supporting people with information and resources will be essential to providing a safety net for movement.

Last night I searched for a job as a Tracer and found this information in the job description:

Contact Tracers will use a web-based client resource management (CRM) platform to reach out to contacts of patients diagnosed with COVID-19 with the goal of documenting a symptom check; referring contacts for testing according to established protocols; and providing them w/ quarantine guidelines

Indeed – searched on April 17th, 2020

Digital Tracking Approaches

Human tracing can be augmented by technology that helps an infected person remember and report contacts they have had. Here are a couple different approaches.

Tim Brookins, a Microsoft engineer in Fargo, tweaked the Bison Tracker to build Care-19, an anonymous location tracker. It had more than 10,000 downloads in its first 36 hours.

The app can serve as a record for people to remind them where they’ve been if they test positive, and to alert them to possible contacts with infected people. They can choose to share information with state health workers.

Bloomberg – April 11, 2020

Google and Apple have announced a joint effort to enable the use of Bluetooth technology to help governments and health agencies reduce the spread of the virus, with user privacy and security central to the design.

The system uses on-board radios on your device to transmit an anonymous ID over short ranges — using Bluetooth beaconing. Servers relay your last 14 days of rotating IDs to other devices, which search for a match. A match is determined based on a threshold of time spent and distance maintained between two devices.

If a match is found with another user that has told the system that they have tested positive, you are notified and can take steps to be tested and to self-quarantine.

Tech Crunch – April 10

As I continue to read about innovations, I intend to share them in the context of how they derive from and serve our most basic needs. While our instinct to meet these needs is active even in good times, the pandemic has us on high alert. We have to find new ways to meet familiar needs. Behavior is goal oriented. We act in order to fulfill our needs; sometimes for social good, sometimes for our selfish satisfaction. Sometimes pro-actively and sometimes reactively.

Next to safety and security, the need for belonging and affiliation is another need on high alert. In keeping with the directive of 6 foot social distance and safe at home, we are inclined to find ways to socialize and connect. In future posts I will describe some of the new ways that we have found to bridge this gap.

Personality and Technology Adoption

In recent posts, I’ve described some factors that guide tech adoption. My perspective of adoption behavior is informed by research, my personal habits, and my observations of others’ habits. The research implicates personal (personality) factors guiding adoption behavior – and success.  This isn’t a radical view and really sounds like common sense. Who we are; what we do for a living, our interests and passions, friends, goals and upbringing shape our values and reflect what we adopt. Added together, these factors appear to form an adoption profile. I’m going to call my approach a “technology personality inventory”.

“individuals construct unique yet malleable perceptions of technology that influence their adoption decisions.” (Understanding Technology Adoption: Theory and Future Directions for Informal Learning – Straub – 2011)

Considered together, multiple models of behavior change provide helpful clues to adoption habits. My goal is to create a model that is practical, in that it helps me understand a person’s adoption habits in action. In casual conversations, classes, and 1:1 consultation, I have opportunities to hear how people view their technology. I primarily talk with family (of all ages), students from 40-84, and colleagues who work in technology. The conversation usually includes these questions:

  • what they are using?
  • what they use it for?
  • how well they understand it?
  • what is their skill level?
  • how much they enjoy or dislike the tool?
  • what do they feel/think they need to know to improve?
  • other tools they have considered for this and other tasks?

While my interviews are not formally structured, I have developed a habit of asking and listening to answers to these questions. My approach comes fairly natural. As a behavior consultant, I assessed the behavior of children based on their emotional / cognitive understanding of people and the environment. An important part of my behavior analysis was understanding the motivation of my students. Operating on the assumption that all behavior is goal oriented, I listened closely to students explanation of what they like and what they avoid. I listened to teachers describe behavior incidents; what occurred before, during and after the event. As I develop a model for understanding adoption behavior, I believe that I can refine my inquiries and the insights revealed. As I apply my behavior analysis skills to my work in technology, the following theories (presented in chronology to their development) seem helpful:

Theory of reasoned action – (TRA) Developed by Martin Fishbein and Icek Ajzen (1975, 1980). Model for the prediction of behavioral intention, spanning predictions of attitude and predictions of behavior. The theory was “born largely out of frustration with traditional attitude–behavior research, much of which found weak correlations between attitude measures and performance of volitional behaviors” (Hale, Householder & Greene, 2002, p. 259).

TPB is an extension of the TRA and includes an additional construct, perceived control over performance of the behavior. TRA and TPB both assume the best predictor of a behavior is behavioral intention, which in turn is determined by attitude towards the behavior and social normative perceptions regarding it.

I agree that intention is a key to understanding the direction of choice. Understanding a person’s intention, their hopes and fears (social, technical, economic, access) says much about where they are headed. Intention is a broad concept and represents many forces. Clearly, humans exchange intentions and model evidence of our choices to one another. This creates a sort of feedback loop of adoption that shapes the diffusion of innovation. This phenomena has been revealed in recent descriptions of mirror neurons. This is a very hot topic within the field of neuroscience. Mirror neurons are ignited in our bodies/brain when we observe someone performing a behavior or using a tool. This was first uncovered in the 1990s in monkeys.

The Technology Acceptance Model (TAM) is an information systems theory that models how users come to accept and use a technology. The model suggests that when users are presented with a new technology, a number of factors influence their decision about how and when they will use it, notably:

Perceived usefulness (PU) – This was defined by Fred Davis as “the degree to which a person believes that using a particular system would enhance his or her job performance”.

Perceived ease-of-use (PEOU) – Davis defined this as “the degree to which a person believes that using a particular system would be free from effort” (Davis 1989).
TAM replaces many of TRA’s attitude measures with the two technology acceptance measures— ease of use, and usefulness. TAM has been revised (TAM2 and TAM3). Ease of use and usefulness stand out as helpful concepts to consider in

The Matching Person & Technology Model (MPT) was developed by Marcia J. Scherer, Ph.D. beginning in 1986. It organizes influences on the successful use of a variety of technologies: assistive technologyeducational technology, and those used in the workplace, school, home; for healthcare, for mobility and performing daily activities. Specialized devices for hearing lossspeecheyesight and cognition as well as general or everyday technologies are also included. Research shows that although a technology may appear perfect for a given need, it may be used inappropriately or even go unused when critical personality preferences, psychosocial characteristics or needed environmental support are not considered. The Matching Person and Technology Model is operationalized by a series of reliable and valid measures that provide a person-centered and individualized approach to matching individuals with the most appropriate technologies for their use.

While it has been primarily applied to special populations in need of assistive technology, it describes factors that apply to any person. Let’s face it, we all have our quirks, abilities and “disabilities”. Our abilities differ by degree and are more pronounced in different situations and different technology. Steven Hawking may have physical limits but he is adept with the technology he has adopted.

When matching person and technology, you become an investigator, a detective. You find out what the different alternatives are within the constraints. —From Living in the State of Stuck: How Technology Impacts the Lives of People with Disabilities

This describes my role as behavior consultant. I applied my detective skills (playing Sherlock Holmes) with my students, trying to uncover their triggers and motivations. My focus was in helping the student to adapt to the demands around her. Needless to say, the ideas within the MPT model are very familiar to me. Instinctively, I pay attention to learning styles, abilities, receptive and expressive communication modes.

As important as it is to understand the personal stories of people adopting technology, it is equally important to consider adoption from a more general theory. Specifically, it’s helpful to consider the macroscopic, social arc of adoption. The Diffusion of Innovations theory is just such a perspective. Often referenced in conversation about technology adoption and marketing. Central to diffusion is communication and the rate at which an innovation moves into the general population. The saturation of an innovation has influence over it’s adoption. As saturation increases, it creates feedback to people at all stages of adoption; Innovators, early adopters, early majority, late majority and laggards.

Diffusion of Innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread through cultures. Everett Rogers, a professor of communication studies, popularized the theory in his book Diffusion of Innovations; the book was first published in 1962, and is now in its fifth edition (2003).[1] The concept of diffusion was first studied by the French sociologist Gabriel Tarde in late 19th century[2] and by German and Austrian anthropologists such as Friedrich Ratzel and Leo Frobenius.[3]

Rogers - Diffusion Model

Roger’s work asserts that 4 main elements influence the spread of a new idea: the innovation, communication channels, time, and a social system. With the advent of social networks, the vectors for innovation have increased dramatically. Social media adoption has become a enabler to technology adoption in general; wheels creating wheels.

I’m excited to apply these perspectives in my conversations with my students, family and random people I meet. It will be interesting to see the patterns in these technology personality inventories. I intend to share my findings along the way. Stay tuned!