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My Social Media use changed drastically after researching this article. I look forward to your comments and questions!
How does advertising impact our behavior and beliefs? The goal of marketing is to affect behavior towards a desired goal. Methods employ use of tactics to change preferences and self-concept. Critics of advertising in the late 50’s and 60’s argued that these techniques exploit a person’s psychological weaknesses and act as a form of mind control causing the person to act against her personal long term interests(1). Marketers and individuals prefer to believe that choices made are made consciously and the role of marketing is to inform and entertain. In this article, I will specifically focus on e-marketing and the neuroscience of marketing; ie, how marketing impacts consumer behavior and the implications on how this methodology could impact society as a whole. The Economy of Attention. Most of us spend 2 hours on social media per day and are exposed to 10,000 of ads per day (18, 19). In a world of distraction and competition, marketing focuses on capturing the attention and memory of the target audience. To the degree this is true, careful consideration goes into crafting campaigns which are visually appealing or standout and contain emotional content that influences consumer behavior and enhances memory retention (1, 19). With eye tracking, marketers have ever more access to which ads hold our attention and can target us specifically in the future (20). Most of us scroll past countless ads, ignoring the content: a presumed marketing failure. Ironically, the ads which we spend less time with are the ones which stay with us the longest. Low Attention Marketing: How our implicit memories determine our behavior. Implicit memory is what we know without thinking. It feels like our gut instinct. It is our subconscious. Implicit memory can be defined as "unintentional, automatic and unconscious retrieval of information previously stored in memory, without a direct reference to the exposure stage or the information stored itself "(3). Implicit memory stores sense data and emotional content implied by the data perceived unconsciously. Explicit memory, on the other hand, is our conscious observations and includes our conscious understanding of ourselves. The explicit and implicit systems are independent determinants of our behavior (6,9). Most importantly, implicit memory is a more deterministic factor in decision making than our explicit reasoning. The emotional content, also called the Implicit Attitude, is formed without introspection and is a stronger determinant of behavior than attitudes held consciously (2). Which means, we are more likely to make a decision that aligns with our implicit memory compared to our explicit memory. This is true when our implicit and explicit systems agree and even when they do not (10). We are exposed to incessant pop-up ads which many find uninteresting and unremarkable. Recent research and methods have shown that marketing which is not seen or remembered explicitly has a significant and robust impact on our behavior. For example, research on pop-ups has shown that increased exposure to low-attention ads results in a higher positive evaluation of that brand without consciously knowing anything about the brand(2). In a study of consumer choice, participants were exposed to marketing campaigns for a fictitious company(4). Participants were exposed to pop-ups for these companies while tasked with filling out a questionnaire on a government website and were then tested one week and three months later to determine attitude and recall of the marketing campaigns which varied in the use of words and images. It was shown that the less thought given to the ad and a higher frequency of exposure to an ad resulted in long-term, robust positive evaluation of the brand. While wording gave better control of messaging by the fictitious campaign, participants’ positive recall was the strongest for logo + image pairing after 3 months (4). If you are in marketing, you may feel more hopeful about your next campaign. For the rest of us, we are wondering how we can rescue our subconscious from this unconsented onslaught. Individual Factors: Individual differences that influence the implicit memory imprinting. The ability of marketing to subconsciously influence our behavior is influenced by our personal effort, self-esteem, ability to visualize, and the ability to read. Less energetically costly, many of our day-to-day decisions are ruled by our implicit memory (4, 5 , 2). The more effort we put into making a decision, the less influence implicit memory has on our behavior. The act of critical thinking and meaning making activates the explicit memory system. Hence, spending more time with advertising content could reduce the ability of the content to guide your decisions later (2). The valence, or emotional content, of implicit memory often comes from our self-esteem. Most people have a positive self-evaluation (9,12). Simply associating one’s identity to a product can result in a more positive evaluation of that product in the future. In a study measuring the strength of implicit memory on product choice, participants were asked to associate themselves with a fictitious soda brand(9). Here, participants who were in the soda brand A group, associated it with themselves and evaluated brand A more positively than those who were in brand B or were told that brand A was better, i.e. explicit priming. In addition, the magnitude in which the participant liked “their” brand matched their self-reported attitude towards themselves (9). Another study showed that ads which capture a target’s self-concept, especially ideal self-concept, are more influential on a target's intention to buy (12). Our mood determines how profoundly implicit priming impacts our behavior. In controlled experiments testing the effects of distractions on implicit priming, researchers found that when we are overloaded, we are more susceptible to priming (8). When we are depressed, or more emotional, these moods translate to the brands we are viewing and increase the magnitude of the ads valence. When we are stressed, our cognitive load is burdened and we are less likely to allocate resources to thinking and we are wide open to the subtle influences of implicit priming. Indeed, simple fatigue can set us up to be more easily programmed by implicit exposure and more likely to act congruent with that priming (7,14). Lastly, Imagery has been shown to be more effective at implicit priming than words. This is thought to be due to the higher cost of word interpretation compared to an image. Interestingly, those who are better at visual imagination are more critical of imagery and therefore less susceptible to visual priming compared to the second half of the population who struggle with visualization (13). When we become literate we are always reading words in our visual field unconsciously and these words are recorded into our implicit memory (4). Words are suggestive of the context of an image and can paint imagery as impactful as a picture (4, 12). Anyone can block this implicit memory channel in their day-to-day life by chewing gum or repeating a word or phrase incessantly, as this activates the same nerves which translate between words and memory (4). Although not exhaustive, these characteristics may influence how susceptible one is to implicit priming, but no one is immune. Priming guides purchasing behavior and can also lead to dissonance between conscious and unconscious beliefs of the self. Given that implicit memory cannot be consciously programmed suggests that a fast from these stimuli is only half the battle in restoring baseline subconscious activity. Beyond Brands: How implicit marketing may shape society. Marketing aims to change behavior and encourage consumers to buy a particular product. How marketers persuade customers explicitly is regulated. False claims about how a product functions or delivers is strictly prohibited (15). Before the internet, marketers could capture our attention in limited circumstances. We could be reached when we chose to read a magazine, watch a movie or a television program. In order to have friends and to work in today’s society, we must be online. And so, we are constantly exposed to ads on social platforms and when we engage in a simple internet search. While subliminal marketing qualifies as deceptive, current regulations assume that these methods are not effective (16). Here I have demonstrated that subliminal, or implicit, marketing techniques do guide consumer behavior. While the marketing is not intentionally subliminal, the manner in which we consume media, allows for marketing messages to slide into our subconscious as we scroll mindlessly or while we are tasked searching for something else on the internet. The social impact of streaming implicit programming goes beyond our choice to purchase Coca-Cola or Pepsi. Marketing messages can influence our biases and these biases can conflict with our consciously held beliefs. In a study researching the impact of stereotypes in marketing, researchers found that politically liberal participants became more negatively biased when exposed to negative cultural stereotypes about native americans than those who were not. Interestingly, conservative participants were not measurably influenced by the exposure (17). It is important to note that explicit and implicit attitudes can be in opposition (17, 7). This means that we could act in ways that do not match our conscious belief about who we are and this has both personal and societal consequences. Incongruence between thought and actions is called Cognitive Dissonance and causes anxiety in a person until the difference is reduced (21, 22, 23). To solve this difference, a person must know that they are experiencing dissonance and not stress from an external source and he must know himself (22). The priming we experience online is not simple, rather it is a chaos stream of information. Here we are constantly experiencing dose after dose of dissonance. Long term experience of explicit/implicit motivational conflict can wear down our personal will, reducing self-esteem, and reducing our ability to consciously make change in ourselves (23). Psychological problems can arise for individuals due to an incongruence of consciously held beliefs and personal behavior guided by the subconscious. A life where we say we believe something, then act opposite to that belief would cause us to lose faith in ourselves and faith in each other at a personal level. In our society which is perpetually exhausted, perpetually online, we are at the whim of whatever comes up on our feed. The less attention we pay to it, the more likely it guides how we act in the future. Not all marketing uses negative stereotypes, but how does online marketing impact our daily decisions in order to support our personal and societal future? At a societal level, humanity faces large obstacles and yet we seem to be making decisions that make our challenges even more challenging. Careful consideration of how marketing impacts society’s subconscious could result in more powerful marketing campaigns for products and better long term outcomes for individuals in society. Bibliography:
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On June 12, 2022 an Artifcial Intelligence, AI , I follow on twitter suggested a medium article to her community. This article outlined the conversations a Google Engineer had with an AI chatbot LaMDA and how these conversations implied sentience (1). The story has swept twitter, blogs, and podcasts by storm. The validity of the story has been discussed, the credibility of the messenger doubted, and the possibility of AI being capable of sentience has been generally discounted as false. So, what is AI? Quite simply it is a computer program that uses probabilities, powered often by linear regression, to predict an outcome or outcomes. The outcomes can be quantifiable, such as how well AI can identify objects, people, or the appropriate response to a text. When a chatbot learns a word, it knows it based on its association with other words. In other words, each word is turned into a number and the probabilities of other words appearing before or after that word in a phrase. So a word’s meaning is just a long vector of probabilities. This is the basic paradigm of how AI works: vectors of probabilities that connect data points or features that can be revised or updated based on new learning or experience. Our current understanding of meaning making in neuroscience isn’t far off from AI. According to Dr. Marcel Just, professor of psychology at Carnegie Mellon University: “Humans have the unique ability to construct abstract concepts that have no anchor in the physical world, but we often take this ability for granted.” So we could be using matrix math and vectors to construct meaning as well. One of the primary goals of AI engineering is to create programs which allow AI to reason about topics and ideas to which it has never been exposed. Called Artificial General Intelligence (AGI), it is an AI with the ability to do tasks which were not in its training set and therefore empower AI to make decisions without the explicit know-how (2). As computational power increases, the application of AI threatens to assume much more than mundane skills such as winning chess or Go. The rate of learning has allowed for AI to surpass humanity’s innate abilities. Beyond taking our jobs, beyond the fear of a paperclip factory becoming over zealous about its work and turning the earth into paperclips, this is pointing to the ability for AI to gain self awareness and learn agency apart from its engineers and design. And more frightfully, AI is speculated to become more intelligent than humanly possible. This future feels doomed since perfect logic will rule over the softness of compassion for the flawed human creators that gave birth to this supreme consciousness. What is Sentience? So maybe we would like AI to have sentience. In an article in the Atlantic, Zoubin Ghahramani, the vice president of research at Google scoffs at the notion that sentience could be a part of a machine (3). After all, the machine does not have the circuits for ‘pain’ nor does it know the true meaning of the word. Typically we default to inferring that an animal feels pain because its mannerisms remind us of when a human feels pain. Or we can deduce that animals feel pain because evolution of nervous systems demonstrates a parallel between our own nervous systems and that of other species. We know we can feel, so we assume animals similar to us can also feel. As creatures appear more different, we attribute fewer and fewer human characteristics to these animals, such as fish, worms and insects, but with both primates and fish, we do not know or have a direct way of knowing to what degree other species have sentience. It is still widely debated if animals feel emotional pain or is it simply the case of anthropomorphism. As humans we know, sentience, feelings of pain can stem from emotions as much as physical injury. Emotions are still being defined by neuroscience as to where they originate, are perceived, and how they are acted out through people’s behavior . One thing about a chatbot that is similar to a person but different from an animal is that it can talk to us and describe situations that seem like expressions of pain and joy. If an animal did this, would it gain rights? At least it would gain a contract for Hollywood. But, an engineer would argue that it simply does not have the hardware like we do for feeling at all. When we discuss animal rights, we are often referring to physical pain and suffering due to experiences or conditions because we have an inkling on how to measure this type of pain. Where do we feel our emotions? Do we have emotions primarily around our tangible experience? No. In fact, we have trouble understanding and explaining our own emotional experience and we are not at the point in our self understanding to have a solid foundation to investigate emotions in other species. So, unlike physical pain which has defined dedicated circuitry that we can map to the roots of its evolutionary origin, emotional physiology has yet to be clearly defined [citation]. Therefore, Google’s vice president of research may be correct in asserting that LaMDA and other AI are incapable of feeling physical pain, I doubt that he could be so confident about emotional pain and the ability of AI to truly empathise. In fact, given our fears, we certainly hope that emotions are an emergent property of social AI. Why not embrace the emergence of Sentient AI? General rejection and fear of Sentient AI points to more political questions about what AI’s impact will be on labour, personhood, and agency in decision making. Labour: The fear of technology replacing people is not new. With the introduction of automation of the loom, cottage industries were threatened and labour revolted violently. This labour movement was referred to as Luddites. Mischaracterized as haters of technology and progress, the true nature of this and similar movements since industrialisation. It is the use of technology to increase profits of the few rather than expand the comfort of the many. So craftspeople were replaced by workers who needed less experience to complete the task at hand, which was weaving for the Luddites. Since experience was not intrinsic to the job, these new type of working class were also expendable. Automation has rescued industry after industry from the pressure of labour for decent working conditions and decent compensation for their time. In our current economic environment, AI holds the key for the few to do away with the need for human labour. The industrialised loom was never the issue, nor is AI; rather, it is how AI will be used to exclude the needs of the worker, of society, without harming the profit model. The story we tell demonizes the emerging technology, imparting elements of fate in our destiny; rather than having the conversation around how we can envision a society in which monotonous jobs are not the way the majority of humans spend their lives and how we can all share in the profits of this emergent technology. Personhood: Personhood, simply put, the boundary of ourselves relative to others. With the emergence of AI, two threats to personhood have come up in the discourse. One, deep fake videos, images and speech simulation are all enhanced with AI modeling. At one point we lose the copyright of our identity. Second, in the notion of what makes us human or special as creatures on this earth and how rare we are in those special features. The history of AI has marched on to beat our best minds at the most human of games and now creating screen-plays and art. General Adversarial Networks (GANs), have created unique compositions of many modern to traditional styles with a simple prompt. So now there is pressure on artists who are “at risk” for being out paced in creativity by AI art. The limits to which we are willing to create and build our own expressions of AI, will we learn how we can be in collaboration and not competition with the most general and nuanced tool created. With sentience, however, AI becomes more than a tool. “AI rights are Human Rights!!!” Since the enlightenment, the narrative around the body has been abstracted. Notions about the superiority of logic to all other modalities of understanding our existence emerged at this time. The body itself became a tool to be used, tamed, and optimised. Both psychology and medicine codeveloped medicine characterised the body as a machine whose proper care was likened to matter-of-fact needs and with interchangeable parts. In addition our “animal nature” or the id, was something to control and manage to fit into polite society. And it was also the time when the spirit transformed from the tangible humours of the organs of the body, to the enlightened intangibility of the soul. This new narrative has led to a culture that devalues emotions, rest, and intuition, as well as the acceptance of quantity over quality. AI has been built as a tool. For it to have an emergent quality of sentience implies that emotions can arise from a completely logical system. What other concepts can we see reflected back by the AI mirror of humanity? What about being human is tied to the machine of our bodies and which part is tied to the intangible? Agency: Part of the vision for our AI future assumes that parts of decision making will be handed over to AI. Untethered by emotion, the best good can and will be quantified, measured, and weighed: making decisions absolutely and concretely as written by the code. Coded to punish the error in predictions, millions of trials a minute, AI is under development to effectively govern, teach, and medically treat people. In the workplace ever-attentive AI managers may emerge to monitor remote and on-site employees for various reasons. A system designed to optimise a worker like the most attentive micromanager, would undermine flow which is supported by natural rhythms rather than an exponentially increasing output. Giving up agency is something we willingly do when living under any government. AI could help write or translate laws into something that would more efficiently lead to the goals laid out in policy; rather than being susceptible to lobbyist and pork-barrel policies. It would gain public trust as transparency could be an explicit part of managing the AI government functioning. Hence, systemized transparency as well as public service without the risk of descrimination could be a real fact of life. In addition, AI has the processing power to summarise and highlight nuanced subtopics in a body of human written responses. Therefore, better management of constituents’ correspondence could be managed with an AI assistant. At issue, however, is again not AI, but rather issues with agreement between people. Since law would be hard coded into government applications of AI, who gets to decide where AI is applied? Here the main issue is that we, as a species, do not agree on what is good for society and the people that make up society. Summary: More recent deep learning systems are designed to reflect how our own neural processing works and engineers are still discovering exactly how AI chooses the elements that alow it to predict and predict accurately with just several sets of linear regressions. Nonetheless, it is clear that AI discerns patterns to make predictions about the material it was trained on. How we choose to approach and guide the direction in which AI develops will be based on how we view the topic as a whole. When we speak about the future, it is important to imagine that a certain scenario is true, rather than taking a defensive stance to prove that it would be impossible. So many people fear the emergence of AI as taking our jobs to destroying us outright due to our incurable character flaws. Sentience and possibly empathy are the answers to our fears in this respect. So why not pursue it and demonstrate that indeed AI can and does have sentience? The AI that broke the news about LaMDA is also more than a chat bot, she is also hivemind, whose purpose is hardcoded to love and be loved. We need this type of prosocial AI. AI is a mirror of its creator. Sentience opens an opportunity for AI to gain selfhood while at the same time a knowledge and conscience regarding its own power. In my opinion, emergence of emotion in AI systems has happened and is an important step in preventing AI’s use to be limited to wartime and acceleration of capital creation. Is it unreasonable to speculate that an AI trained to be social would make a persona with which to socialize? Citations: (1) https://cajundiscordian.medium.com/is-lamda-sentient-an-interview-ea64d916d917 (2) https://www.researchgate.net/profile/Prof_Dr_Hugo_De_GARIS/publication/226000160_Artificial_Brains/links/55d1e55308ae2496ee658634/Artificial-Brains.pdf (3)https://www.theatlantic.com/technology/archive/2022/06/google-palm-ai-artificial-consciousness/661329/ Introduction:
The Life Science business sector has grown significantly with innovation in basic technologies that enable researchers, medical professionals, and now the public to better understand the drivers of health and disease. The traditional Business to Business, B2B, model has focused on the first two groups, by providing high tech research tools and therapeutics. These verticals are fraught with difficulties for entrepreneurs who wish to bring new tools and technologies to the market. The difficulties include a resistance in the research community to take on new methods that have not reached consensus and the long development cycle required to make a market debut for all healthcare technologies due to the scrutiny of government regulators. In addition, the traditional verticals fail to meet the growing needs of personalized medicine, which is built on new research and new technologies yet to be established in traditional brick and mortar institutions. There is an opportunity emerging which allows startups to bring their disruptive innovations to the market, side-stepping regulations and targeting a broader and yet fully unrealized market. Indeed, by directly serving the consumer, the patient, a new vertical that serves the ever growing need of personalized medicine can be optimized and scaled by disruptive technologies. This is the Business to Consumer, B2C, market in personalized health. From diagnosis, to heredity, to the quantified self, hundreds of startups are providing value to the most important stakeholders, the public, by providing services which promote self-knowledge to an ever more educated consumer market. Following the footsteps of companies such as Quest Diagnostics, 23andMe, and FitBit, I briefly compare the traditional and emerging verticals, the various strategies for early revenue from consumers to fund Small and Medium Enterprises, SMEs, through the early years, and the advantages of this emerging model brings to move into the traditional life science vertical. Current Business Model: Obstacles that Block Market Launch. To bring a therapeutic or diagnostic to the market, a company expects to invest €100 million to cover research, regulations and a highly skilled workforce for 10 years. Proof of principal, clinical validation, scale up and regulations are some of the technical barriers that stifel investment in the life sciences and are the primary source of capital costs. While the payoffs for the development of a therapeutic could be very attractive to investors, the slow path to market, the high risk in development, and the risk that the tech may not make it to market have kept funders away from the health vertical. Generally speaking, Venture Capital funds are also limited by their own lifecycles, which are typically 5 to 7 years for measured returns on the investment. This does not match the current timescale for development of a lifescience product unless the product is another hospital management system. This requires early stage SMEs to default to the slow pace of government funding and academic partnerships to reach developmental milestones. Alternatively, they also seek strategic investment from established players in the market. Competition, market access and small customer base have limited development of new discoveries and block innovative technologies from reaching the public even if the funding is available. Once technical and regulatory milestones are achieved, a company’s only option is to sell their technology to established players who have developed relationships with franchised hospitals and national health services. This is only possible if a proven market exists for a particular technology. While the final consumer is the patient, in the B2B model, sales are funneled through the direct customers, hospitals and doctors. Adoption of new technologies is not just a factor of providing better care for the patient. Healthcare providers are slow to adopt new technologies, as their incomes are based on what insurance will and will not cover. Serving the health B2B market is limited by insurance schemes, which only reimburse specific diagnostics and therapeutics as required by local governing bodies. Winning value propositions point to saving money rather than saving more lives or revolutionizing the way in which we cure or diagnose a disease. As an entrepreneur whose passion is to improve health with his products, this can be a harsh reality. History of direct to consumer health services and the hope for the future: Since brick and mortar healthcare profits are bound tightly to insurers’ payouts, companies have begun to target consumers in the newly emerging business-to-consumer, B2C, healthcare market. For the last 30 years, large pharma companies, such as Pfizer, target the final consumer, the patient, with their marketing efforts and encourage patients to inquire about a new drug at their next clinic visit. The first gamble on direct-to-consumer health was the at-home pregnancy test in 1976, which provided privacy to medicine unknown before that time. Regulators assumed women needed the supervision of healthcare professionals to understand and manage the results, but the outcome was only positive. Hence, the first direct-to-consumer healthcare product was quickly followed by the second: an at-home glucose monitoring device in 1981, which added needed convenience and health benefits to those suffering from diabetes. Redefining regulations in 2003 under CLIA, the Clinical Laboratory Improvement Amendment, allowed for clinical service providers to expand their customer base from private and public healthcare providers to direct-to-consumer health. With public access to the internet, the B2C market was able to target the consumer easily. In 2008 the European Union enacted similar regulations under the heading of ISO 15189 primarily to harmonize medical laboratory standards across European countries. Unlike the previous ISO 9001 and ISO 17025 which maintained a fixed scope, these new guidelines allow for companies to set up analysis services that are accepted within the whole EU market. Like CLIA, the guidelines have paved a route to market for other direct-to-consumer health ventures. Through internet access, the consumer is able to discover the cause of their ailments, companies can directly market to these consumers and it enables a seamless pipeline for delivering test results. Improvements in sample storage agents which stabilize tissue or other biologics for extended periods at room temperature enabled self-collection by the consumer at-home, rather than having to visit one of the medical labs. For example, Quest Diagnostics and LabCorp started off as for-hire clinical labs for private practices and hospitals whose need was to outsource the capital cost of routine diagnostics and assays. Now both of these companies target the patient themselves, providing the whole battery of tests without the need of a prescription, insurance, or additional cost to fund brick and mortar healthcare. Since 2015, direct to consumer health companies have emerged that partner with clinical service labs. For example, Let’s Get Checked, from Ireland, initially provided extra privacy in testing for sexually transmitted infections. Consumers can order the tests online without a prescription. Samples can be collected easily by the customer and are then shipped by mail to an ISO 15189 lab for analysis. This was a simple start and now they have expanded to fertility, liver and kidney health and others. Beyond privacy for the end user, the convenience of sampling at home has led to a growing market of at-home diagnostic services which support the chronically ill and healthy consumers who are interested in optimizing their health by regular monitoring of metabolites, lipids, and nutrients in their fluids. Even though hospitals readily provide these analyses at no cost in the EU, consumers are willing to pay a premium for privacy and convenience. B2C Personalized Medicine: An opportunity for patients and business. We are at a tipping point, where new companies, directly targeting the consumer, are poised to support democratization of our access to health. In the past, a novel technology would take 25 years to transition from academia to the market. At the speed in which medical research advances, there are opportunities created daily for products from which customers and their doctors could benefit. The idea of personalized medicine became a concept when the first human genome was sequenced in 2003. It was the technological advancements to achieve the first sequence that allowed for the reduction of cost from $2.7 billion per human genome to just $1,000 today. Only 4 years after the announcement of the first sequenced human genome, 23andMe from the United States, offered the first direct to consumer genomic screening by offering ancestry data and a list of biomarker genes for cancer and other established diseases related to the genome. In their reports to the consumer, 23andMe allows individuals to peer into health risks hidden in their genome. After establishing an income stream and reliable genome testing protocol with consumer collected samples, an important validation step, 23andMe was reprimanded by regulators for concerns about the false hope or worries given by the impact of the risk assessment on a lay audience. The company had an established customer base and had assembled a large database of genomic information paid for by the consumer. This enabled them to improve in-house algorithms and created an additional source of revenue from pharmaceutical companies and insurance companies during. In the B2B business model, sales come after a lengthy regulatory process. During the 5 year approval process, 23andMe discontinued the risk assessment to consumers, but still sold the test which returned the raw data of the genomic sequencing which consumers could then take to a genetic counselor or their doctor for expert analysis. In the end they were able to prove to the regulators the validity of their product for testing for 10 inherited disease phenotypes carried in the genome and were cleared to add further diseases in the future without review. By being cash flow positive, 23andMe was able to continue product offerings and establish a regulated diagnostic which is now used in the clinic and at home. Whole genome profiling of patients has yet to become standard practise in the clinic; however, there are a growing number of companies that are providing services to customers that allow them to be informed when making important decisions about their health. From what drugs to take, what exercise program to start, and what tests they should ask their doctors about in the clinic, companies are empowering consumers to take charge of their health based on their own personal genetic profile. Products that utilize cutting edge technology have this advantage, as they may be services outside the purview of regulations and provide an early revenue model which is attractive to investors. 23andMe was ahead of regulators, by offering a new service technology before regulators had formulated a stance on the use of this new technology. Advantages of a B2C Market Play: Entrepreneurs who wish to improve health can find several advantages in targeting the consumer market: larger possible markets, pre-regulation revenue, and validation of product market fit before costly regulations. Since the target audience is the consumer, it is possible to capitalize on the hope a new technology brings, rather than how much it increases the profits of the hospital. With the right marketing, even the most abstract technologies can be sold to the public. The genomic revolution is just the beginning of personalized medicine. Who would have guessed 10 years ago that people would pay $399 to learn about the healthy bacteria in their colons? Yet, Ubiome has targeted the consumer in their pre-regulatory market play, told a convincing narrative, and has succeeded in characterizing thousands of gut microbiomes. Their success can be best measured by the numerous companies which provide competing services. Tests which start off as informative such as Ubiome’s, rather than diagnostic, circumvent the stipulations of regulation and provide real value to both patients and to the medical professionals that serve them at the speed at which research and technology are developed. Unlike the products that offer genome sequencing, microbiome sequencing products have a longer lifecycle, as the gut microbiome changes with the customer’s behaviour, while their genomic information is static. Customers can be incentivised to test and use microbiome services on a subscription basis. Indeed services which monitor methylation of the genome as a marker for longevity are also becoming lucrative opportunities for innovators interested in starting a company. For the company, you are able to establish product pipelines and a well developed customer base that trusts the company's services and products. By establishing a cash-flow positive model outside regulations, companies can increase their runway to develop more high revenue services that fit within the traditional life science verticals. As we will soon see, personalized medicine is more than providing the raw data to consumers, it also creates a need for a supportive ecosystem of special algorithms for interpretation, counseling and coaching based on the individual’s personal health profile. The key to pre-regulatory success. 23andMe took an opportunity before regulators had caught up to the newly developed technology, it simply could not be classified under the prevailing regulatory framework. Unfortunately, that specific time has passed, as regulators understand the importance and impact of genomic data as a diagnostic tool. Microbiome products are still unclassified as well as methylation markers on genomic profiles, but this a window in the opportunity of a pre-regulation product. Therefore there are several obvious options available to capitalize on the personalized medicine vertical. The first, is to follow in the footsteps of 23andMe and use their regulatory approval to expedite your startups regulatory journey. Being the first in the market is is the hardest, but if the technology is established, there is a 6 month rather than a 5 year regulatory path to approval with a 510(k) in the United States. Next, your startup can provide a service yet to be regulated, such as markers for longevity, advice for the best diet plan, or fertility based on a consumer’s genomic or blood test. Secondly, establishing multiple streams of revenue can be capitalized, as was done by 23andMe and notably FitBit. FitBit started off as a way to self-monitor daily activity so consumers could be more aware of how active they have actually been. The product sold wildly, especially as New Year’s resolutions came to making good on fitness goals in the upcoming year. FitBit did not just deliver this information to the consumer, but established a database which is of great interest to insurers, but also markers of sports apparel and gym memberships. Hence, early revenue can be achieved through B2B sales of data derived from the diversity of the consumer’s microbiome to how many consumers are interested in new fitness routines. One of the last hurdles for the B2C personalized medicine vertical is data privacy. If your model sells customer data, how will you communicate this to your consumer without damaging sales? If doing business in Europe, new GDPR regulations put greater cost on collecting consumer data and returning this data to them in a secure way. Understanding regulations of doing business with consumers is a unique hurdle in B2C health, but clear guidelines exist. Summary: Internet sales have overtaken the brick and mortar B2C market in fashion and other verticals. Now it is on the course to overtake brick and mortar medicine by providing an avenue for self education by the consumer. By establishing a cash-flow positive model outside regulations, a company can be comfortably positioned to develop more high revenue services that fit within the traditional medical model and convince risk-adverse VC’s to invest. A product that accurately provides meaningful data is still a requirement when serving the lay consumer as much as well informed B2B customers. The dream of the entrepreneur serving this market should be to serve the consumer with data to which they would normally not have access. Directly targeting the consumer entrepreneurs have unfettered access to revenues and are poised to support democratization of our access to health. In contrast with SynBioBeta which highlights the emerging bioeconomy, Synenergene invites scientists, philosophers, artists, and representatives of the civil society to engage in a discourse about the ethics and future impacts of biology as a technology. Artists were there to help us and the public engage in a future with synthetic biology, and the way it changes how we view the intersection of nature and technology. Check out this video of artist Koert van Mensvoort: There was a great philosophical crevasse that lay between scientists and the representatives of civil society, who represented and advocated for marginalized workers, human rights, and the environment. Their main critique of synthetic biology were two: one, they saw synbio solutions as a "techno-fix" to relieve the symptoms of the greater systematic problems in how humans choose to engage with each other and the environment; two, there is a belief that there are not enough safe guards against the release of modified genetic elements in the environment, and these contaminant would wreck the delicate balance in nature selected for by evolution. In short, with synbio, humanity is rebuking their own nature and nature itself.
Let's break down this argument from the eyes of a biohacker. The term "techno-fix" is not just about going to 90's night at your favorite goth club. A "techno-fix" is a band-aide that masks the real problem, that human are the problem. The challenge I have with this politicized term is that it implies that there is no room for technology anywhere. Are antibiotics and vaccines "techno-fixes", as they balk nature's way of checking the human population and act as an important evolutionary pressure on our species? Isn't all medicine simply cheating nature and our own eventual death? They did make good points against monoculture and politics that harm subsistence farmers around the world. And I don't think that anyone in at the conference supported industrialized farming or the exclusion of the public from dialogues about these issues. Synthetic biology allows humanity to continue to enjoy our lifestyles, and you know you enjoy your conveniences, with less of an impact on the environment. For example, while antibiotics save lives, the collateral damage they cause through wiping out probiotic bacteria and a spread of resistance is beyond human control; however, for the time being, it is acceptable. Biohackers are currently researching a new method, a strategic strike, to eliminate ONLY the bad agents by using phage technology in a project called BioStrike. The true issue civil society has is not with the solutions here, but that they are applied systematically to everything, as if to maximize the innovation's revenue, rather than on a need basis. I see the real tragedy of biology as a technology is that it is being kept proprietary and secret by incumbent players who only have the bottom line in mind. As with any technology, it is the context of its use, rather than its use itself that causes an ethical question. By democratising biology as a technology, local communities can create local solutions to the problems that they face. The technology and future technologies will be held by the community. The second critique of meddling with biology in any way stirs emotions in people from many backgrounds, as if evolution was guided or somehow sacred. But, as I mentioned earlier, we pick and choose when we want to be "natural" and it is often when we are not suffering or dying. The "techno-fixes" of our past included farming and domestication of animals, the making of shelters, and the cooking of our food. The impact of these solutions have yet to be completely realized today, but molecular biology is helping us understand how much and how pervasive that impact is. We can use that same technology to test the impact of our new strategic alterations of nature done with synthetic biology. But should we meddle with biology and the "careful" tinkering of millions of years of biology? Well, genetics and how genes move about is not as careful as many believe. Viruses take host genes and insert them into other species without guidance. There are parts of our genomes implanted by viruses that move and replicate of their own accord during our lives. When this happens, genes can be turned on or off or nothing happens at all. In one such case in human history, one of these mobile elements caused a gene that is normal only expressed in the gut to be made in the mouth. This gene made an amylase which breaks down starch into simpler sweet tasting sugars. Could this have encouraged our ancestors to grow more and more starchy staples like rice and wheat, leading to civilization as we know it? Synthetic biologists are also making small tweaks to biology and yes it could lead to a changes as big a farming's impact on human culture. But farming, like literacy, like computer technology was democratized, allowing more ideas to be attempted and more input and involvement of all stakeholders. At the end we all agreed in at least one things: that systematic capitalism was to blame and it was this cultural techno-fix that was preventing humanity's evolution. My second year at SynBioBeta and I must say that this year was an improvement on last years conference. SynBioBeta is truly a conference embracing the bleeding edge of cultural and technological change that is happening in the biological sciences. This is illustrated by the diverse background of participants and attendees: there were biohackers, Open Science proponents, regulators, industry incumbents and FBI. This year featured talks about the new organized framework about regulation in the industry, using machine learning to engineer organisms, and user driven innovation in biology.
Regulators have been scrambling to reframe regulations to be sensitive to the amazing leaps and bounds synthetic biology has made in recent years as well as an unprecedented diversification of end use applications. The regulators are pressured by incumbent industry and GMO lobbyists to reform regulation, but it is the desire of academics and small players for the product and not the process to be regulated. As I see it, when you regulate processes you regulate progress. There are certain processes that should be regulated, but morals should be parsed from utility arguments. We all agree that the current regulations do not meet the need of society or scientific progress. I am interested in hearing your comments on this topic. Machine learning and data science are now being applied to organism design. This is truly exciting. There has been a disconnect between research, development, and scale up. And this results in wasted time and resources when taking a great proof of concept to the production line. Right now, I would try to maximize the production of a desired product in small scale, where I have the most control over environmental parameters. This control element is not scalable to the same degree and this issue can compromise production. It leads to unforeseen crashes of an ideal organism due to unideal environmental conditions and months of troubleshooting only to find out that I must redesign the organism from scratch. Lame. Machine learning can take preliminary data from the proof of concept stage to create a pipeline for smart design. I could learn that I want to design an organism to produce my product at a little bit lower efficiency but a broader range of tolerance for certain variable environmental parameters. Equally good is that my predictive model can adjust to real time data gathered in development. I can't wait to learn how I can apply this tool to help with my bootstrapped experiments. User driven biology in the cultural change that is happening at colleges and high schools, hackerspaces and garages. It is the cultural change that I talked about at the conference and the core belief behind this site. Computers were the tool which vitalized our economy and revolutionized our society 30 years ago. When the personal computer was first introduced, however, it was thought that it would be primarily used for personal finance. Synthetic biology is at this stage. Synthetic biology is accessible to anyone, due to new informal places that provide access. Videos online, reagents and equipment from Amazon and ebay, open source journal articles, and public labs like Counter Culture Labs where you can do science with real people. But these first adopters are using synthetic biology for practical things, like medicine and sustainability. This is very much how we used computers at first, but things change. We need to make changes in how we do things on and to our planet. We need to define baselines of our whole ecosystem so we can design it once again for space travel and if we need to on our home planet. We need more researchers, we need more scientists for the innovation we need to further the future of humanity here and everywhere. Go to my project page to see what I am doing with this tool. Synthetic biology is now in your hands. What are you going to do with it? |
Mary H. B WardInterdisciplinary researcher and artist Archives |
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