The Asian coronavirus strategy

What happened?

As the coronavirus sweeps across Europe and the United States, it seems that Asian countries are handling the crisis more successfully. South Korea deployed mass testing to control the virus and Singapore has recorded zero deaths with one of the oldest populations in the world. To explain the success of some Asian countries, many commentators point to their strong governments and “lockdown” measures. However, South Korea never even locked down its most affected city (cafes, bars and gyms remained open) and Singapore mandated “self-quarantining”. Indeed, we have to look beyond the idea of “strong governments” to explain Asia’s relative success.

What does this mean?

To be sure, not all Asian countries are successfully dealing with the coronavirus. Across Southeast Asia, in countries such as Thailand, Malaysia and Indonesia, the response has been chaotic and disorganized. The strongest responses have been from East Asian countries, including Singapore and Vietnam, in what Bruno Maçães calls the “Confucian cosmopolis”. Largely based on the 2003 SARS pandemic, these countries have deployed “early warning systems” with “fast response policy”. Taiwan, for example, took quarantine measures as soon as the first Taiwanese became infected. Most importantly, besides strong government responses, there is broad-based support in these Asian countries for drastic measures like social distancing and GPS tracking. Indeed, rather than a model for an authoritarian state, South Korea defines its model as a “dynamic response system for open democratic societies”.

What’s next?

The coronavirus reveals that high trust in Asian countries leads to strategy that is more effective. Interestingly, one consequence of high trust in government is a different role of technology. To battle the coronavirus, the most interesting innovation has emerged from countries such as China (automatic temperature detection, Alipay Health Code) and South Korea (drive-through testing pods, self-monitoring apps). As technology is rooted in cosmotechnics, the current crisis forces us to look beyond the coronavirus to imagine a different technological future in Asia. We can expect Asian tech companies to benefit, as Asian governments and citizens are more willing to experiment with innovative technological solutions to the coronavirus.

Corona and the US healthcare system

What happened?

The United States are struggling to contain the Corona outbreak as its government has little oversight over actual infections and the spread of the disease. One reason for this, some have claimed, is that the millions of Americans with no or limited healthcare insurance are reluctant to see a doctor or take a test when they show (mild) symptoms of infection. They are afraid of medical bills for tests, further treatment and the costs of quarantine measures. At least one patient already received a bill for more than $3.000.

What does this mean?

In contrast to some of China’s more drastic measures, e.g. locking down entire cities, most Western nations take a relatively relaxed approach to fighting the virus outbreak. All of this centers around early detection of individual cases and monitoring those who they been in contact with. In the US testing took off slow due to manufacturing problems and a lack of clarity with respect to the coverage of costs. Only last week did several states and private insurance companies announce they would cover all costs of testing (still leaving the uninsured with no coverage at all).

What’s next?

Healthcare is already a major theme among the Democratic Presidential candidates with Bernie Sanders pushing for a national health insurance program and Joe Biden seeking to restore and strengthen Obamacare. The Corona outbreak, when it escalates further, could very well sway more Americans to support a more inclusive health care system. Not only because it would benefit currently uninsured individuals, but also because of collective interests in a healthy and well-monitored society.

The (un)changing doctor-patient relationship

Sapere aude, the famous phrase of Kant generally translated as “dare to know”, could be marked as the institutional start of democratization during the Enlightenment. Man rid himself of his immature beliefs and grounded his life in reason and argument. In the following two centuries, this self-liberation of citizens led to empowerment in most cultural, political and economic institutions. Remarkably, health institutions stayed significantly behind. Healthcare became institutionalized and more widely available, but when it came to understanding our own health, all citizens remained laymen, helpless when confronted with illness. Therefore, scholars and physicians have repeatedly advocated the democratization of the doctor-patient relationship to empower patients and promote their self-reliance. With the advent of digital health and the internet, the empowerment of patients seems to be partially achieved, but not every part of the relationship can or should be democratized.  

Our observations

  • The internet is a great source of health information but searching for an explanation of our symptoms can be a real hassle. Healthcare start-ups such as Ada are trying to address this problem. The company has created an AI-powered tool to help patients with their self-monitoring and health management. Once you have typed in your symptoms and answered a series of questions, the AI calculates and displays the likelihood of possible diseases, based on a growing database that matches your age and gender. The app makes clear it doesn’t officially diagnose, but only supports the process of self-monitoring. 
  • In the digital age, self-tracking for health is no longer the exclusive province of chronic patients or fitness geeks but has become widespread. Almost every smartphone OS has apps to make basic measurements in the background of our daily life. Consequently, even without explicit health goals, we’ve all started to collect valuable health data. On the one hand, these new flows of data have resulted in digitally engaged patients and have increased their autonomy. On the other hand, health data is often privately owned and part of wider disciplinary programs or monetization strategies from companies or states, which does not always empower patients.  
  • Nowadays, placebo effects mainly have a negative connotation, as they are associated with false clinical results. However, according to this article, this reputation is slowly changing. Instead of debunking the non-medical effects, we should embrace the psychological effect of placebos in medical treatments. The underlying argument is that emotions trigger biological processes and should not be seen as something separate or non-relevant. These triggered interactions of neurological, immunological and hormonal processes interfere with medical treatments and could strengthen or diminish their effect. In other words: medical treatments would be more efficient if doctors were aware of the importance of attributes that evoke positive emotions, such as trustworthiness, intimacy, authority, wisdom, etc. Not as something important besides the medical treatment, but as an inherent part of it

Connecting the dots

For more than half a century, scholars have envisioned and advocated the democratization of the doctor-patient relationship. In short, it means the shift from paternalistic doctor-centered medicine to more democratic and patient-centered medicine. While the first is characterized by authority and knowledge asymmetry, the core principles of the second are equality, mutual participation, long-term engagement, the patient-as-a-person (instead of a biological reduction), and shared decisionmaking. These principles should result in clear benefits for the patient: empowerment, autonomy and, importantly, better health outcomes, because who knows the patient better than he knows himself. 

Although the scientific discussion of democratization can be traced back to the ’50s, in the last two decadesdigital health has enabled the empowerment of the patient. It started with the internet and Google. Information about health and disease is only a few mouse clicks away. Within minutes, patients can acquire information about any symptom or disease. And then wearables arrived on the market. To measure is to know. Endowed with wearables and dwelling in environments packed with sensors, citizens now continuously collect health data, monitor biometrics and self-diagnose disease. As well-known cardiologist Topol describes in one of his latest books, the patient is evolving into a sort of COO of his own health

The rise of informed, connected and engaged patients in the daily practice of healthcare has also evokedcriticism of democratization. Physicians who once strongly advocated it have become more reserved because they see patients turning away from expertise, demanding second opinions and overly trusting data. Furthermore, scholars are questioning whether we really want patients to interpret their health datathemselves and stress that we should take into account how this will affect them mentally. All in all, having more digitally engaged and participatory patients is undeniably beneficial to healthcare. Yet, some nuance and differentiation are warranted

First of all, neither of the terms in the equation refer to fixed entities, which means “the physician” and “the patient” don’t exist. Naturally, some relationships might become more democratized than others. A lot of severe conditions demand expertise and clinical interventions, which leaves less space for participation. However, in the treatment of chronic long-term diseases such as diabetes, shared decisionmaking and engaged patients can be extremely helpful. The same holds true for the minor illnesses and everyday care general practitioners and nurses are often occupied with. For them, having well-informed and engaged patients constitutes a good starting point, eases the conversation and speeds up the care process. 

Second, health and disease are becoming more complex and multidimensional. For instance, comorbidity (i.e. when someone is diagnosed with multiple diseases or conditions at the same time) is occurring more frequently and will be one of the main challenges of 21st-century healthcare. In light of the above, it is tempting to perceive democratization as a fruitless campaign with anything more complex than a simple virus or cold:patients simply haven’t studied medicine for eight years. Still, it might be useful to reflect on the participatory role and think about what we can reasonably expect from patients. For example, the mere process of collecting health data and monitoring biometrics, without interpreting the data, is already meaningful. Patients can manage their health database and preselect important metrics, perhaps supported by Artificial Intelligence. This patient-AI alliance could focus on selecting risk factors, early detection, and disease prognosis. The doctor arrives at a later stage. In this scenario, democratization is not so much direct empowerment of the patient, but a telehealth feature that mainly serves to streamline care paths. The ultimate challenge here will be to keep false positives within manageable rates. With everybody connected and always monitoring, we might prevent more, but also detect more, and time is one of the most precious assets in healthcare. Besides the cost of overdiagnosis, it also worries people unduly.

This brings us to the third point of nuance. In the ultimate sense, democratization refers to the ideal of a mutual and equal relationship with minimized knowledge asymmetry. However, the role of physicians far exceeds their knowledge, they are “healers” in the broadest sense of the word. Healthcare is the sum of effective therapy and moral care. Physicians and nurses always transcend the medical practice in a way. They listen to the patients wishes or worries, guide them through their illness and thereby help people reconcile with their disease. In this context, an unequal and asymmetric relationship isn’t problematic but instead beneficial for patients. It is about the doctor we trust and rely on, and who has a special sort of spiritual or even religious air about him. Furthermore, all his words, procedures or his mere presence could elicit placebo effects. Consequently, the “disenchantment” with the doctor as a result of overly enlightened citizens could undermine the mental care provided by physicians. Of course, the (placebo) effect of healers is modest with most major medical conditions, but especially in long-term chronic disease management, mental healthcare, and psychosomatic pathologies, this beneficial side of an asymmetric doctor-patient relationship should not be underestimated.  

To conclude, if we want to fully reap the benefits of democratization with engaged and well-informed patients, the doctor-patient relationship first needs to be differentiated and dissected. Subsequently, some parts of healthcare systems could be democratized while other parts remain untouched.

Implications

Higher health expectations of demanding patients and extremely engaged health citizens might eventually result in a sort of boutique healthcare, comparable to the currently rising “boutique fitness”. However, part of this trend is the loss of middle-market companies, only very expensive small boutiques (e.g. David Lloyd, Saints and Stars, and Gustav Gym), and low-cost mass-market gyms (e.g. Fit for Free and Basic fit) will survive in this market segment. It is questionable whether this outcome is desirable for healthcare. 
With the advent of digital health, who becomes in control of which health data has become a pivotal topic of debate dividing stakeholders and scholars. Topol argues that if we really want to realize the benefits of the digitally engaged patient, we should give patients the right to own their medical data. He points to blockchain technology and cooperative organizations such as HealthBank to support this transition. By contrastinteroperable data systems and integrated services are perhaps best developed and operated by big tech companies such as Apple. 

Smart Tattoos

What happened?

Tattoo-like medical sensors are being developed as low-cost and practical alternatives to more cumbersome blood tests, wearables or implantable devices. These sensors, which are either applied to our skin like a temporary tattoo or injected beneath the skin like a real tattoo, can deliver real time and continuous measurements of, for instance, electrolytes and metabolites in sweat, plasma, saliva or tear fluid. Such sensors are already used by diabetes patients to monitor their glucose levels and the future may see many more applications, even including markers related to (types of) cancer.

What does this mean?

The patch-like sensors are highly flexible, stretchable sensors and can last for weeks, virtually unnoticed. They provide rich data on a range of parameters. Most use electrochemical techniques to measure a physiological parameter and connect to a separate device to store and display results. Others are able to measure minute movements and can be used as elaborate activity trackers (e.g. in rehabilitation processes) and can also be used to generate power for other sensors (i.e. energy harvesting). In another class of sensors, experiments are also ongoing with ink-like material, such as engineered human cellsthat change color in response to specific molecules. These are thus actual tattoos that produce directly visible “measurements” on the surface of human skin.

What’s next?

These temporary tattoos and sub-skin injections augment our skin with an additional interface. While our skin can already display embarrassment or nerves (blushing) and other emotions such as fear (goose bumps) as well as more serious conditions (so-called flushing), these applications create new possibilities to quantify ourselves. Obviously, most applications will be strictly medical and applied only to those with a direct medical need, but on a more speculative note, we can imagine how these kinds of tattoos could end up becoming interactive body decorations or even be put to more malign use as, for example, publicly visible lie detectors or alcohol testers.

Commercial DNA databases in search of a new business model

What happened?

Privately held companies Ancestry and 23andMe hold some of the world’s largest collections of human DNA. These companies were able to build such large databases in a short time because millions of people bought their DNA kits in order to find out about their ancestors, potential health issues or other personal traits that can be found in someone’s DNA. However, by now the initial hype surrounding their services has faded and sales have stagnated, forcing 23andMe to lay off 100 people.

What does this mean?

In part, the decline of these companies may be related to growing privacy concerns among the general public. More likely, their problems also arise from the fact that they have little to sell beyond a single test and, as it stands, they have no recurring revenue from their early adopters. In response, these companies are looking to develop new tests for their existing customer base. These tests could cover other diseases and may even include traits of our personality. The CEO of 23andME, for example, says she’s determined to make inexpensive genetic information available without medical professions getting in the way. At the same, these companies try to connect with pharmaceutical companies and academic research groups so that they can create precision medicine together. So, in order to stay profitable, these companies expand their activities and collaborations with third parties.

What’s next?

The privacy matters that come with surrendering one’s DNA to a private business are still underexposed considering the depth of the (potential) information and the scale of the databases that are built by these companies. Although, for example, 23andMe promises to safeguard this private information, there are already a few examples in which a large DNA collection of a privately held company was used for purposes that its consumers didn’t anticipate. In the case of the golden state killer, for example, the FBI gained access to the database of GEDmatch that could find the suspect even though he never participated in a GEDmatch test (some relatives did). When these companies are in need of new business, their data-filled treasure chests will be extremely valuable for, amongst others, health insurers, the pharmaceutical industry and governments. We can easily imagine how this could result in a slippery slope as privacy concerns are challenged by potential society and commercial gains.

A viral virus

What happened?

A new coronavirus outbreak in China recalls the 2001-2003 SARS outbreak, which took about 800 lives and cost almost $40 billion. This new outbreak is likely to spread even faster because of the increased mobility of Chinese people. Take, for example, the growing Chinese middle classes that can afford airplane tickets (e.g. international departures from China grew over 10 times between 2001 and 2017) and the expanding Chinese high-speed railway network (the number of Chinese railway passengers has grown exponentially in the last decade, to over 3 billion annually). Moreover, the outbreak coincides with China’s very busy Spring festival. As a result, this new coronavirus’ infection rate is much higher than that of SARS.

What does this mean?

However, the adoption of digital technology provides reason for optimism. When SARS broke out in 2001, the Chinese government was accused of concealing the case. But with Chinese netizens actively posting about this new outbreak on social media, China’s government cannot hide the outbreak from its people and the rest of the world, forcing it to respond much faster (e.g. WeChat allows users to report incidents of the virus and inadequate measures). Furthermore, real-time data of patients (e.g. their whereabouts, symptoms) could enable authorities to implement much more effective measures (e.g. quarantining more specific areas), while AI helps to track and predict the spread of the contagious disease. Lastly, using the smartphone as an interface for telehealth services, many patients can now diagnose themselves with the disease, increasing the chances of early detection and treatment (e.g. Alibaba and PingAn offering free online consultations).

What’s next?

We have written before that despite the promises of the internet (e.g. freedom of speech, democratization), what has materialized is the opposite (e.g. surveillance capitalism, digital repression) and the internet is in need of a transition.  However, in times of crises, the bottom-up approach of internet and social media still proves to be a powerful force. To illustrate, the Iranian government was forced to acknowledge that they shut down the Ukrainian International Airline Flight PS752 after it took off from Tehran because of social media posts that reported on the crash. And as data has a will of its own, showing evidence of things we like and do not like to measure, it prevents actors from concealing the truth when things go wrong (e.g. Swedish radiation monitors alarmed the world about the Chernobyl disaster). Furthermore, open data that can be scrutinized by non-public and -private parties can help uncover malpractices and protect citizens, thus granting them freedom and more empowerment.

Value based healthcare

In an attempt to improve the quality of healthcare services and curb rising costs, a transition towards socalled value based healthcare is set in motion. This new paradigm is all about rewarding healthcare providers for their actual contribution to peoples health, instead of paying them for whatever they do, irrespective of the outcome. This transition calls for institutional innovation, e.g. a shift of risks from insurers to doctors as well astechnological innovation towards highly interoperable data systems across the sector. Because of these challenges, and more fundamental objections against the paradigm, it is no wonder that the transition is only moving ahead slowly.

 

Our observations

  • The concept of Value Based Healthcare (VBHC) was popularized by Harvard professors Michael Porter andElizabeth Teisberg in their 2006 book Redefining Healthcare. Their main critique of the healthcare sector was that there was no system of outcomes measurements to monitor the actual value of treatments and hence that a basis for genuine and meaningful competition between providers was missing.
  • The basic idea is to reward healthcare providers for the health gains they deliver instead of simply paying them for the services they provide. Not only does this, in theory, reduce the incentive to provide ever more care (and bigger bills) it only opens doors to cooperation between providers to jointly provide the best (and most cost-efficient) care possible between them.
  • There are roughly two options to organize VBHC. One is to bundle multiple services required by a patient in the case of a specific condition (e.g. tests, treatments, follow-up checks) and to reward a (group of) provider(s) according to the outcomes of this bundle (i.e. a so-called episode of care). The other option is “capitation” and entails healthcare providers taking responsibility for all the health needs of a group of people for a fixed fee per capita. In both options, provider(s) who save costs, while maintaining or improving the outcome, get to keep (a part) of the savings.
  • Countries across the globe have started to experiment with VBHC and introduced policy incentives to stimulate its implementation. While many stakeholders claim to work on this basis (e.g. commercial insurers in the U.S. claim that over 60% of their claims is part of a VBHC contract), in practice change is much slower as VBHC is only introduced in mild forms (with providers taking few to no risks) and mostly related to specific conditions for which the effect of treatments is highly predictable. One organization claims that true VBHC payment systems only account for some 4-6% of the U.S. healthcare system (and the Netherlands is also slow to adopt).
  • Actual proof of cost savings is scarce. A recent meta-study concluded that, within the American Medicare system, value based healthcare only resulted in measurable savings for hip and knee replacements(1.6% lower costs from 2013 to 2016). CMS (the Medicare administration) claims annual savings of $739million due to VBHC-like initiatives. Another, non-academic, study concluded that U.S. healthcare payers who implemented VBHC realized 5.6% savings.
  • The Dutch diabetes clinic Diabeter is a much-applauded example of VBHC; an patient-centred model in which all care is organized around the patient (instead of a patient being sent from provider to provider). DIabeter is among the best performing clinics and realizes cost savings as patients spent less time in (expensive) hospitals.

Connecting the dots

At its core, the shift to Value Based Healthcare is a shift from processes to outcomes and a shift from medical gains in the narrow sense to health gains in the broadest sense (including quality of life as perceived by the patient). Together, these are expected to lead to higher quality of care and lower costs as a result of better cooperation between healthcare providers (e.g. within or between hospitals) and quality-improving and cost-saving innovation.

While it may sound rather simple, the successful introduction of VBHC requires a paradigm shift in the way the healthcare sector deals with the division of tasks between stakeholders. This is especially true for the relation between the payer, typically the state or an insurance company and different kinds of health care providers. Inthe traditional services-based model, the healthcare provider is free (roughly speaking) to choose whatever test or treatment deemed necessary and costs are reimbursed by the payer. This implies that the risks of additional costs, for instance due to complications or the occurrence of multiple conditions at once (i.e. comorbidity) aresolely with the payer. Hence, there is no incentive for doctors to consider the most cost-effective options. In the VBHC model, risks are partially shifted to providers as they are expected to help the patient against a fixed fee, even when additional treatment is necessary. At the same time, they stand to benefit from relatively “easy” patients and smarter and more cost-effective ways of helping patients. The latter relates strongly to the fact that, in the new paradigm, healthcare providers are incentivized to work together to jointly improve quality and lower the costs. That is, fees are defined on a higher level of aggregation than today (e.g. for a pre-definedepisode or the entire healthcare needs of a patient per year) and providers need to distribute payments between them and, hence, they have a shared interest in improving quality (to get paid at all) and lowering costs. As part of this institutional paradigm shift, technology can play a crucial role to monitor health outcomes (i.e. both in terms of technologically measurable health and perceived quality of life of the patient) and to coordinate efforts among providers. This implies highly interoperable data systems and willingness to share data among providers and payers.

Exactly because this requires a paradigm shift, change is far from easy. Healthcare providers are reluctant (and often financially unable) to take on risks that are currently taken by insurers and governments. This is why VBHC programs are still limited to conditions for which risks are wellknown and limited and most (or all) care can be provided by a single organization. More complex conditions such as heart failure, are far less likely to see VBHC contracts in the near term. More and better data, and hence better risk assessments, may change this in the future, but there is a bit of a chicken-and-egg dilemma as better data is most likely to result from VBHC programs in the first place (i.e. joint efforts to monitor a patient’s progress across multiple providers and over longer time spans).

There are also several moral objections against the concept of VBHC. One is that it is unclear what “value” actually means, for example, the monistic business concept of value neglects personal values, and who is entitled to define the concept (e.g. a doctor measuring health or the patient experiencing health). Another, often-voiced, concern is that VBHC tends to undermine solidarity in the healthcare system. Healthcare providers will be reluctant to take on high-risk patients whom they are unlikely to cure within the pre-defined budget (e.g. because of likely side-effects). Although this is not allowed in most countries, instances of “patient dumpinghave occurred. Moreover, it is probably easier to force insurers to take on customers (as in most countries today) than it will be to force providers to take on patients (as they could, in some cases, argue that they would not be able to cure them). And last, VHBC presupposes a participatory informed subject making rational choices. Although research confirms most patients prefer to participate in their care process, it is still unclear to what extent this is desirable.

In response to these objections, mere cost-savings by reducing overtreatment may not suffice to convince the general public and healthcare providers (some of whom fiercely oppose VBHC for said reasons). A more convincing argument could be that prevention can play a bigger role in the healthcare system when both payers and providers have a shared financial interest in the general well-being (i.e. not getting ill) of “their population. This is certainly true in the case of capitation when providers take on the responsibility for the full medical needs of a group. It will also play a role for lifestyle-related diseases for which providers than have an additional incentive to make sure patients life healthier after they have been treated.

Implications

  • Despite the lack of evidence, VBHC is being promoted globally, e.g. in the Netherlands, the EU and China.Even though this may not result in radical cost savings (immediately) it is likely to lead to a surge in data about treatments and their outcomes (including patients’ own assessments) and this could form the basis of better (and possibly cheaper) treatments in the future.
  • VBHC could enable more investments in e-health solutions by healthcare providers (e.g. hospitals) as they could actually benefit from resulting savings (i.e. lower costs or health improvements) that end up with other providers or insurers in the current system.
  • One problem with VBHC is that it (implicitly) relies on the assumption that overtreatment is a significant problem and a major factor in rising healthcare costs. A recent paper argued that the real problem (in the U.S.) is that many pharmaceuticals are too expensive, administrative costs are running out of control and doctors are paid too much (in comparison to other developed economies. Big Pharma is already of out favor with the general public and doctors may face the same problem.

 

Retroscope 2019

The end of the year is a time for contemplation. In this Retroscope, we look back and reflect on the ideas and insights we have published in The Macroscope throughout 2019. We have covered a wide range of events and developments in technology, global politics and society. The Macroscope is marked by our team’s diversity of perspectives, ranging from philosophy, economics, history, sociology, political sciences to engineering. Combining this interdisciplinary approach with scenario thinking, we aim to assess current affairs from a comprehensive and long-term perspective. Our retrospect of 2019 is therefore about how this year’s events tie in with or deviate from larger trends in technological, hegemonic or socio-cultural cycles. Our mission is to unlock society’s potential by decoding the future.

We hope you enjoy our reflection!

FreedomLab Thinktank

Click here for our Retroscope of 2019.

 

Click here for our Retroscope 2019: Hegemonic cycle

Click here for our Retroscope 2019: Technological cycle

Click here for our Retroscope 2019: Socio-cultural cycle

Click here for our Retroscope 2019: Disruption in the making

Retroscope 2019: Disruption in the making

Disruption in the making

In 2019, we have written about how four domains of our daily lives are being disrupted by digital technology: mobility, health(care), food and education. In all these cases, digital technology does not only change the competitive field and reshape value chains, it also changes consumer preferences and creates new social and ethical challenges. As digital technology, regulation, consumer practices and business models co-shape each other, disruption is a process continuously in the making.

1. Mobility

Despite all stories about new generations not caring about cars, very little is changing in our travel behavior. Youngsters have less money and study longer, but as soon as they earn a living and start a family, they display “adult travel behavior”, just like their parents.

For now, we should not expect too much of technological change either. Even though chipmakers are getting ready to build a chauffeur-on-a-chip, it’s been a challenging year for self-driving cars and it will take many years before truly autonomous vehicles hit the road for real. Until that time, they will operate in trials to collect data for training purposes and possibly, within limits, for last-mile solutions. Most of all, they will be learning about the difficult-to-predict behavior of other, human, road users. Even if self-driving cars eventually come to work perfectly, it is still questionable whether we will welcome them wholeheartedly. For now, technology developers encounter quite a bit of resistance and even technology vandalism that reminds us of the Luddite protests in the early 19th century.

On a different note, the push for electrification of road (and waterborne) transport continues, because of climate change and in response to growing awareness about the deadly impact of local air pollution. Next year, we will see a surge in the number of electric vehicles on the market, but demand remains highly dependent on local subsidies for consumers and ethical concerns over natural resources (e.g. cobalt) could dampen enthusiasm about EVs. For this reason, and because battery technology will not progress fast enough, hydrogen as a fuel-of-the-future made quite a comeback last year.

2. Health

We are in the midst of the transition to a more personalized, preventive and participatory healthcare system. Changing disease patterns and aging societies demand a different organization of the system. Naturally, all eyes are on digital technology when it comes to enabling the transition, but, as we’ve frequently noted, digital technology is not a solution in itself. To illustrate, smart home care could relieve pressure and reduce unnecessary and costly hospital visits, but we expect socio-cultural dynamics, such as the coming generation of self-conscious and tech-savvy “elastic” elderly, to also play a big role in the sustainable management of aging societies.

Furthermore, ubiquitous digital self-tracking practices empower citizens to take responsibility for their own health, keep patients better informed on their health and could thus help democratize the doctor-patient relationship. Unfortunately, the rise of self-tracking might also lead to coercive practices and exploitation of the more vulnerable groups of society and government policies could be perceived as patronizing.

On an existential level, we don’t really know what the impact of the datafication of life will be. The emergence of the quantified self might improve measurable health, the amateur athlete is starting to look like a pro and the widespread adoption of mindfulness apps might help us get rid of the self-destructive and easily distracted “ego”. At the same time, the lack of spiritual legacy in mindfulness could increase self-centeredness or lead to alienation from our very own bodies.

For these reasons, socio-cultural reflection on the role of technology in health care is indispensable. Clever algorithms are already able to outperform doctors on specific and limited tasks (e.g. diagnosing tiny lung cancers), but we don’t expect doctors will be replaced altogether. The decision-making process of doctors requires moral reflection, practical wisdom and they have an important “healing role”.

3. Food

In 2019, food became a pressing geopolitical matter. We saw how the trade war between China and the U.S. disrupted food trade flows, how several conflicts around the world caused food insecurity (e.g. in Venezuela, Yemen and Sudan), and how countries increasingly looked to secure their future demand (as shown by China’s investment in agriculture in over 100 countries).

Unsustainable pressure on earth’s resources is further threatening food security. We are urged to look for ways to produce food in a climate-smart way: by adapting to climate change (e.g. saline farming, climate-resistant crops or regenerative farming practices) as well as reducing the ecological footprint of the food sector (e.g. fighting food waste or reducing food packaging). Drawing most attention this year were alternative protein products, as the plant-based protein transition is gaining speed in developed countries. Yet, since middle classes are rising across the developing world, demand for animal protein is bound to increase, as is illustrated by the rising popularity of milk in China.

Global obesity levels continued to rise in the past year and, in response, we are increasingly in search of more healthy lifestyles. What we eat is key to our health, attempts are emerging to biohack our diets and people have sought ways to link diet to our DNA.

As more and more people are moving to cities worldwide, the question is who the next generation of farmers will be, especially on rising continents such as Africa, where the rural youth do not aspire to traditional farming and are rapidly moving to cities. The question is also how growing cities will be able to sustain themselves in the future and what role indoor farming will play in this challenge. Meanwhile, online food delivery in urban centers is disrupting the food chain by challenging the traditional middlemen and sometimes even connecting consumers to farmers directly.

4. Education

Like last year, traditional education systems are struggling to provide students with relevant qualifications for the rapidly changing labor landscape. Consequently, alternative and sometimes radical initiatives to educate future employees are on the rise and companies are increasingly hiring without demanding a conventional degree. Coding, for example, is becoming an important skill for future generations to participate in our ever-digitizing world,but it has not found its way to general education yet. Nor has formal logic, even though it is central to all programming and would help future coders, irrespective of which coding language they eventually come to use. To fill that void, many online apps, programs andgames that offer the possibility to master coding skills are gaining popularity. Meanwhile,EdTech promises to bring about a revolution in traditional as well as alternative education in terms of efficiency, affordability and accessibility. Until now, EdTech has primarily offeredsolutions in traditional subjects such as math, language and geography and not much in the way of the desired 21st century skills.

Click here to see the full Retroscope of 2019

When we really become hybrid beings

Digital self-tracking has some clear-cut applications for specific groups. Most athletes would not stand a chance if they didn’t apply self-tracking to optimize their training schemes and improve their performance. And for certain people with health problems or chronic diseases, self-tracking is essential to the preservation of their health. But what about the rest of us? There are some great advantages to self-tracking, especially in terms of health, but for it to become valuable in the daily life of the ordinary user, two important challenges need to be overcome.  

 

Our observations

  • Some studies have shown that about one-third of users stop using an activity tracker within six months after purchase. The most commonly named reasons among the dropouts: no clear health benefits, irritating instead of motivating features and meaningless data representations. 
  • However, according to Wired, these studies were mainly conducted in when the activity trackers were still quite one-dimensional, had terrible batteries, and most importantly, lacked sticky features. But the flagship wearables of the industry-leading companies are improving rapidly. Software and user experience are starting to get better, more data is aggregated from different sources, data visualizations are becoming more compelling and features more motivating. 
  • In a clinical setting, neurofeedback is a therapy that uses real-time displays of brain activity, mostly through an electroencephalogram (EEG), to regulate and train different brain functions. This is used, for example, to improve the concentration of patients with attention deficit disorder (ADD). 
  • Outside the hospital walls, hypnotherapy apps such as Mindset claim to use neurofeedback with a headphone picking up brain activity. However, scholars question the reliability of this method and even in a scientific setting, the results of neurofeedback are mixed.
  • Although the effects of neurofeedback are questionable, the interface is appealing and promising for self-tracking practices. Often, self-trackers collect data and this data is visually represented and communicated back to the user through a Graphical User Interface (GUI). With apps such as Mindset, the interface is more intuitive, as it works on verbal sensory feedback. The headphone tracks our brain activity and if it realizes our mind is wandering it will play a small tune, so we can refocus. The ultimate goal is to make our brain rewire and for us to automatically refocus before we have completely lost concentration. 

 

Connecting the dots

As we have written before, self-tracking has become omnipresent. For professional athletes, wearables can be very helpful for improving performance and devices with automated sensors can be lifesaving for patients with heart conditions or diabetes. However, for the general audience, self-tracking is often not very spectacular in terms of self-knowledge or empowerment. For most of us, digital self-tracking is fairly one-dimensional and straightforward, we use meditation or sleep apps to improve productivity or sleep quality or wear an activity tracker to improve overall fitness. This status-quo of self-tracking contradicts the implicit beliefs of the self-tracking paradigm: that through the use of wearables we will get to know our inner self better than through our sensory experience and this will empower us in unforeseen ways.

Theoretically, self-knowledge and empowerment are the most important arguments for partaking in digital self-tracking. Technological devices and biosensors are able to expose the mysteries of the body and precisely this potential gain in self-knowledge can’t be detached from the perceived increase in control over ourselves. Knowledge is power, self-knowledge is empowerment. Data insights can be used to act upon it, and thereby change behavior. 

This datafication of life presupposes the metrification of life and, in Western society, numbers have a certain authority and resonance. Consequently, self-tracking leads to the objectification and demystification of our bodies. Ultimately, the idea is that the body will become obedient to the reflexive calculations of the self, “dead” material for gradual improvement and mathematic optimization. 

But what about the real world? If the self-tracking paradigm wants to live up to these high expectations and become valuable for the mainstream, it needs two overcome both a technological and a socio-cultural hurdle

The technological challenge of self-tracking practices is to build multi-dimensional data assemblages of humans, integrated into preferably a limited number of platforms, and with a friendly and visually appealing user interface. This requires a multitude of sensors and the capacity to correlate raw data to actual problems or life goals. From that perspective, the challenge is mostly technical and, barring the privacy issues concerning sensitive health data, gathering and integrating more personal data into a single platform seems a solvable challenge for big tech companies. 

However, whether self-trackers will succeed in mastering the body or end up slaves to their data assemblages,ultimately depends on something else: the way they “negotiate” with the collected data and make sense of it. Self-tracking doesn’t merely represent our body in a visually appealing way, data representations change our concepts of selfhood and embodiment as we become new hybrid beings.

Digital self-tracking causes a partial shift in bodily attentiveness from direct perception to external measurements. Broadly speaking, this happens in two different ways. The first entails a negotiation between a direct sensation and its digital counterpart. Take our heartrate, we feel our heart beating but at the same time observe a number on our watch. The second negotiation is more complex, because, as we stated earlier, trackers and sensors could also reveal things about ourselves which we are not able to sense directly. In a clinical setting, this is an everyday occurrence (e.g. MRI scan, ECG, blood tests, etc.). This second type of consideration will be an incredibly challenging task for individuals who desire to fully exploit the advantages of self-tracking. Data practices demand sense-making of the data and sense-making requires a complex interplay of bodily attentiveness, logical thinking, knowledge, and knowhow.  

Especially with regard to health and disease, we might overestimate our capacities to intervene in a way that’s beneficial to our health. In our society, notions of health and disease are mainly grounded in scientific knowledge and concepts and thus are complex phenomena, often characterized by multicausality. In this regard, 99% of us will most likely always remain laymen and might therefore end up doing ourselves more harm than good. Furthermore, scholars have shown that self-tracking might empower us, but might also have adverse effects. For example, research on sleep apps has shown these applications do more than give a neutral indication of sleep quality. There is a normative aspect hidden underneath the “neutral representation” (e.g. when the app tells people they’ve had low quality sleep, they start to behave accordingly and feel more tired during the day). Instead of empowerment, fixation and dependence on the sleep app are the results. As sociologist Deborah Lupton states, data has a capacity for betrayal. 

We can think of several solutions and paths forward to prevent some of the above scenarios. A pragmaticapproach would be based on trial-and-error: when we don’t know what the reason is for the way we feel or behave, and we don’t ask why, we can change behavior patterns and simply observe whether we improve or not.

Another option might be to try distinguishing and subsequently limiting the consumer applications of self-tracking practices. Solving general health and well-being issues such as returning stomach complaints could be required to have a formal quality mark or an instantly automated referral to professionals. On the other hand,self-tracking devices might be perfectly able to assist us in daily endeavors, for example, helping us concentrateor stabilizing mood swings. In real life, however, this distinction will be hard to make.  

Hence, both options have their pitfalls, but they are pragmatic efforts to realize some of the high expectations of self-tracking without too many drawbacks. Only when that is achieved can self-tracking become really valuable for the ordinary user. 

Implications

  • In the future, more tactile interfaces and interactivity between users and data could make self-tracking more in appealing and intuitive. Neurofeedback, voice tones, and haptic responses are possible feedback mechanisms that don’t require us to constantly “leave” the body by looking at numbers.
  • Wearables aren’t only useful for self-monitoring and self-optimization; their data mappings and visualizations also act as means for self-expression. They play a role in the narrative we tell ourselves and others. In this regard, in the future, data visualizations could become more important in social media and platforms facilitating such forms of conspicuous self-tracking would have a competitive edge.