Their impact is technophobia produced by cognitive bias.

III. PSYCHOLOGICAL RISK PERCEPTION: WHY HUMANS MISPERCEIVE TECHNOLOGY

There are several psychological factors that contribute to risk misperception in humans. People rely on a mixture of cognitive crutches, heuristics, and emotional appraisals to navigate the risks of everyday life.2 15 A brief mental exercise demonstrates one of these cognitive shortcuts. Take a moment and picture a bird in your mind. Chances are you pictured a sparrow, robin, or crow instead of a long-wattled umbrellabird or an albatross. But why did your brain, without any conscious thought, select the bird that it did? Why does the baseball player refuse to wash his lucky socks? 216 Why do Americans perceive Black men as more dangerous than white men? 217

The answer to these questions lies in the mental shortcuts and biases our brain engages in every single day. 2 18 In some cases, they are actually rather successful in assisting humans to process informational inputs quickly.219 In the course of everyday life, one is more likely to encounter a sparrow or a robin, and faith in a lucky pair of socks can sometimes lead to a better outing. But these heuristics and biases are fallible. 220 When you inject complexity into mental processes, such as processing race in America, these mental shortcuts often operate as devastating shortcomings. 221 They can cause humans to act irrationally and systematically misperceive risk.222 As the world humans inhabit continues to increase in complexity, one can expect risk misperception to worsen.223

This Article does not, and cannot, survey all of the different heuristics and biases that might affect risk misperception. The purpose, rather, of this Part is to identify a select few that have an inextricably intertwined connection to certain immutable characteristics of emerging technology, causing a general aversion to such technology in humans. In short, the below heuristics and biases are the driving forces behind systemic technological risk misperception. Compounding the issue, these mental shortcuts are themselves interconnected. Humans often combine heuristics and stack inference upon inference to paint different layers of a risk portrait.224 Only by identifying and understanding the cognitive and psychological factors that contribute to misperception, can humans then begin the process of reducing their impact on decision-making processes.

A. The Precautionary Principle as an Overarching Backdrop to Regulatory Decision-making

The Precautionary Principle operates as the decisional canvas upon which humans employ their heuristic and cognitive shortcuts to paint a portrait of the risks they face in life.2 25 With the post-industrial "emergence of increasingly unpredictable, uncertain, and unquantifiable but possibly catastrophic risks ... ," societies began to formally incorporate the Precautionary Principle into their decisional processes. 226 There is no singular definition of the Precautionary Principle; rather, it occupies a spectrum ranging from its weak form to its strong form.227 At one end, "[t]he most cautious and weak versions suggest, quite sensibly, that a lack of decisive evidence of harm should not be grounds for refusing to regulate." 228 At the strong end, "regulation is required whenever there is a possible risk to health, safety, or the environment, even if the supporting evidence is speculative and even if the economic costs of regulation are high." 229 From these polemical definitions, the parameters of the precautionary continuum can be deduced: (1) the burden of proving the absence or presence of risk; (2) who bears that burden; (3) the scale and probability of the potential harm; (4) whether regulation is required or merely encouraged; and (5) the scale of the regulatory remediation. 230

As the World Commission on the Ethics of Scientific Knowledge & Technology has noted, "the [Precautionary Principle] is a strategy to cope with scientific uncertainties in the assessment and management of risks." 231 It is inherently conservative, creating a rebuttable presumption in favor of the status quo. Its adoption has "marked a shift from post-damage control (civil liability as a curative tool) to the level of a pre-damage control (anticipatory measures) of risks." 232 Although sources trace the origin of its modern form to the 1970s, the Precautionary Principle is really a regulatory endorsement of more colloquial thinking evident in age-old adages such as "better safe than sorry." 233

Examples of the Precautionary Principle in regulatory decision-making are everywhere. It has become nearly ubiquitous in international environmental regulation.234 Given the scientifically uncertain nature of the dangers posed by climate change and pollution, many environmental conventions incorporate some form of the Precautionary Principle.23 5 The Precautionary Principle helps explain why millions of law abiding citizens are subjected to full-body scans at airport across the country every single day.236 It is the same principle that influenced Dr. Kelsey's decision to reject inconclusive data regarding the safety of thalidomide. 37 It is also the same principle that spurs overreaction to the low risk of school shootings. 238 Like any tool of decision-making, the Precautionary Principle must be wielded with precision.

Professor Cass Sunstein, a long-time critic of the Precautionary Principle and preeminent American expert on behavioral economics, has "suggested that the weak versions of the Precautionary Principle are unobjectionable and important." 239 It states a "truism" that combats the kind of decision-making that would require an overwhelming showing of harm before taking action to mitigate risk.240 He warns against trivializing this function, citing a poll revealing onefifth of Americans believe no costly action should be taken against global warming until we are assured of its actuality. 241 In other words, the weak form of the Precautionary Principle is useful in combatting the kind of decision-making that would require an absolute certainty of harm to trigger a regulatory intervention.

In its strong form, however, Professor Sunstein argues that the Precautionary Principle is paralyzing and ultimately useless as a tool of decision-making.2 42 "In some cases, regulation eliminates the 'opportunity benefits' of a process or activity, and thus causes preventable deaths." 43 This phenomenon was evident in the example of FAA-mandated child restraints discussed in Part II. In that case, regulation would have reduced one source of risk (child injuries on airplanes) but given rise to a substitute source of risk (increased motor vehicle travel). "The point is ... [that] in its strongest form, [the Precautionary Principle] is offended by regulation as well as by nonregulation."2 44 "This is a common situation, for opportunity benefits and substitute risks are the rule, not the exception."245

Take, for example, the case of nuclear arsenals. The global stockpile of nuclear arms, ninety percent of which is held by the U.S. and Russia, is enough to end human life several times over.24 6 The mere existence of these weapons creates a risk of nuclear terrorism or even nuclear holocaust.247 Relying on a strong Precautionary Principle, several members of the medical community have called for the total abolition of nuclear weapons. 248 Going even further, one group has declared nuclear proliferation to "be among the most urgent of all global public health priorities."249 As Professor Sunstein cautions, however, a faithful Precautionary Principle analysis must cut both ways.250 The existence of nuclear weapons has contributed to an unprecedented nuclear peace among world superpowers.2 51 If war is merely "a continuation of political intercourse, carried on with other means," then politics for its own sake must always stop short of nuclear war.25 2 Put differently, while an abolition of these weapons might reduce the risk of nuclear catastrophe, a substitute risk of conventional world war would arise. For mutually assured destruction to serve its deterrent purpose, it must be exactly that: assured. 253 Therefore, the strong Precautionary Principle would also seem to counsel in favor of a nuclear triad possessing enough redundancies and weapons to destroy the world several times over. Consequently, a faithful application of the strong Precautionary Principle is paralyzing in this situation because it cautions against both choices. In other words, even if one agreed that it is always better to be safe than sorry, rarely is it clear what is safe and what is sorry.

Sunstein's critique of the Precautionary Principle is nuanced. Again, in its weak form, it is unobjectionable. 254 The absence of a causal link should not always preclude regulatory intervention. In its strong form, it is paralytic and thus cannot be relied upon. 255 Notwithstanding the paralytic effects, however, it still has "widespread appeal." 256 Herein lies the key to Professor Sunstein's critique: how can groups, like the physicians above, continue to embrace the strong Precautionary Principle when it cautions against both regulatory intervention and nonintervention? The answer lies in the fact that individuals "can regard themselves as 'precautionary' only if they blind themselves to many aspects of riskrelated situations and focus on a narrow subset of what is at stake. " 2 7 This blindness or selective risk awareness is possible because of cognitive biases. 258 In situations where the strong Precautionary Principle should be paralyzing because of the existence of substitute risks, humans, subconsciously relying on cognitive biases, selectively apply the Precautionary Principle to some sources of risk while completely ignoring others.2 59 "Simply as a logical matter, no society can be highly precautionary with respect to all risks." 260

The Precautionary Principle (and the cognitive biases that inform its application) is magnified in the context of emerging technologies. The strong form Precautionary Principle should almost always be paralytic in this context. On the one hand, it would require government regulation of any emerging technology that might pose a risk to health or safety. Since the nature and scope of risks posed by a new piece of technology often suffer from a significant degree of uncertainty, the Precautionary Principle could be invoked in favor of regulating nearly every emerging technology. On the other hand, emerging technologies offer potential opportunity benefits. Technology saves lives. Consequently, the Precautionary Principle would caution against any government interference that might inhibit the development of lifesaving technologies. Thus "it [should] stand[] as an obstacle to regulation and nonregulation, and to everything in between." 26 1 The remainder of this section, however, demonstrates how the cognitive biases that inform applications of the strong Precautionary Principle selectively amplify the perceived risks posed by emerging technology in a particularized manner, tipping the decisional scales in favor of regulation. That is, cognitive biases, working through the Precautionary Principle, consistently manifest as a bias against emerging technologies, resulting in suboptimal regulatory decision-making.

B. Neophobia: Fear of the Unknown Versus Dread of the Unfamiliar

It is easy to see how a human penchant for fearing unknown risks could influence the selective application of the Precautionary Principle. The Precautionary Principle is an attempt to account for scientific uncertainties. A fear, or even discomfort, associated with uncertainty could lead one to over-perceive any threat associated with that uncertainty. 262 This cognitive bias is also exhibited in common proverbs, such as "better the devil you know than the devil you don't." In the context of emerging technologies, fear of the unknown takes on a different, amplified meaning. The risks posed by emerging technologies are likely to be overperceived because, not only are they unknown or uncertain, they are unfamiliar and alien.263 In other words, "familiarity may breed contempt: common actions and activities are often not perceived as especially risky compared with the unfamiliar or the novel."2 64 Thus, the very nature of emerging technologies results in a particularized kind of phobia: technophobia-a subset of neophobia. 26 5 As an example, while the risk associated with a tornado or hurricane may be uncertain or unknown, we accept that these kinds of natural disasters are somewhat familiar to us, even if we aren't directly affected by them. So-called "murder hornets," on the other hand, engender a more dreadful kind of fear because they are alien and thus are not easily comparable to other, more familiar, natural disasters. 266 Consequently, the selective application of the Precautionary Principle to emerging technologies is influenced not only by a fear of the unknown but by a dread of the unfamiliar.

Neophobia is well-documented. A risk perception study in Korea revealed that individuals over-perceived the risk posed by the 2002 SARS outbreak relative to the risk posed by influenza because of the unfamiliarity of the SARS risk factors.267 One Canadian study of sexual behavior found that individuals were more likely to downplay the risks of unprotected sex with a hypothetical new partner who they perceived as more "familiar," even where familiarity provided no "information about the sexual health history for any of the hypothetical partners." 268 This study indicates that it is not only familiarity in the objective sense, but in the subjective as well, that determines risk perceptions.269 This suggests that the brain can be lulled into feelings of familiarity even in the absence of true familiarity. Other studies have noted that perceptions of familiarity regarding an ethnic cuisine are negatively correlated with perceptions of risk posed by that cuisine.270 As some of these observers have explained,271 concomitant to a fear of the unfamiliar is the mere-exposure effect, a "well-established finding that people evaluate a stimulus more positively after repeated exposure to that stimulus." 272

Technophobia as a form of neophobia is likewise well-documented. 273 Much of the research surrounding this phenomenon was inspired by a wave of computer-phobia in the 1980s when the age of personal computers dawned.274 It can be defined as "an irrational fear and/or anxiety that individuals form as a response to a new stimulus that comes in the form of a technology .... "275 From a logical standpoint, "the adoption of novel products [or technology] is typically associated with risk taking and uncertainty because accepting novelty implies leaving the realm of the familiar." 276 A literature review of empirical research regarding the impact of technophobia on business concluded that "the introduction of technological changes can provoke emotional and cognitive reactions. This fear and anxiety may manifest itself in the form of a phobia-induced by technology; technophobia." 2 77 In turn, that phobia "might push employees to avoid the new technology." 278 Moreover, "technophobia d[oes] not fade away with time. In fact, new technologies bring new and unique facets of technophobia . . .. 279

Technophobia's influence on risk perception and decision-making is costly. Indeed, looking only at its effects on the workplace, it has been "estimated that technophobia might be responsible for no less than $4.2 billion[] in wages, in the United States alone." 280 Further research suggests that aversion to unfamiliar technology, a heuristic in its own right, is informed by other heuristics.281 In effect, the absence of familiarity results in a blank canvas of sorts, which, out of discomfort, humans subconsciously seek to fill with other heuristics. Turning to some of these other heuristics, it is clear how they comingle and compound one another to bias individuals against unfamiliar technology.

C. The Availability Heuristic

When sorting through unknown or unfamiliar risks, humans rely on the availability heuristic to manufacture risk probabilities. 282 The brain attempts to produce a proxy estimate of the probability of an event occurring or the frequency of a class based on the ease with which prior examples can be recalled from stored recollections. 283 For example, the reason an individual might think of a crow or a sparrow when asked to picture a bird is likely because those examples are the ones frequently encountered, and thus are the most available for the brain to recall. "The availability heuristic illuminates the operation of the Precautionary Principle, by showing why some hazards will be on-screen and why others will be neglected." 284 It helps explain why the Precautionary Principle is invoked against emerging technologies when instead it should be paralytic due to substitute costs.

The availability heuristic can operate as a convenient means of estimating and navigating the risks of everyday life. 285 "[It] is an ecologically valid clue for the judgment of frequency because, in general, frequent events are easier to recall or imagine than infrequent ones." 286 In this sense, it would appear that the availability heuristic is at odds with the foregoing discussion of unfamiliar risk. In general, one might expect that familiar risks would be overestimated by the availability heuristic since they are the most available, whereas infrequent and unfamiliar risks would be underestimated because they are unavailable. "However, availability is also affected by various factors which are unrelated to actual frequency. . . . [S]uch factors will affect the perceived frequency of classes and the subjective probability of events." 287 These manipulative factors are especially prevalent in the context of emerging technologies. When they are allowed to bias human perception, "the availability heuristic can lead to serious errors in terms of both excessive fear and neglect." 288

Any number of factors which affect memory recall can lead to a biased application of the availability heuristic. 289 The most obvious factors are salience and vividness.290 They contribute to availability because the more salient or vivid an experience, object, or story is, the more likely it is to trigger and capture attentional resources in the brain and for longer periods of time.291 "Greater time in thought means more rehearsal, and more rehearsal means greater memorial availability." 292 In the context of tobacco regulation, graphic warning labels incorporating salient and vivid depictions of the adverse consequences of tobacco consumption have been shown to result in better recall of the warning messages.29

The underlying nature of emerging technologies renders them particularly susceptible to a biased application of the availability heuristic. In particular, "[c]ontextual factors such as ... novelty ... or media coverage increase the salience of an event." 294 Demonstrating the interrelated nature of different cognitive biases in risk assessment, novelty and unfamiliarity contribute to availability because new and unique objects or events are likely to capture attentional resources.295 As previously discussed, emerging technologies are, by definition, novel and unfamiliar.296

With respect to media coverage, "[a]vailability, produced by 'a particularly vivid case or new finding that receives considerable media attention,' play[s] a major role in . .. leaps in public concern." 297 Emerging technologies are particularly affected by media coverage because they are subject to the Gartner Hype Cycle. 298 "Gartner's Hype Cycle . . . characterizes the typical progression of an emerging technology from overenthusiasm through a period of disillusionment to an eventual understanding. ... "299 The period of disillusionment often occurs "[b]ecause the technology does not live up to. . . the media's overinflated expectations, [and] it is rapidly discredited. Some of the early trials end in highly publicized failures. Media interest wanes, except for a few cautionary tales." 300 While the technology usually recovers from early struggles, negativity bias-in which "bad information is processed more thoroughly than good"-helps explain why individuals perceive negative media hype as more salient than positive hype. 301

[FIGURE 1 OMITTED]

Finally, the nature of the substitute costs associated with regulating emerging technologies also renders them particularly susceptible to availability bias.3

Sometimes a certain risk, said to call for precautions, is cognitively available, whereas other risks, including the risks associated with regulation itself, are not.... In many cases where the precautionary principle seems to offer guidance, the reason is that some of the relevant risks are available while others are barely visible. 303

For example, the brain can easily understand the causal link between mandatory infant restraints in airplanes and reduced injuries related to flying with infants.304 The causal pathway the brain must navigate, however, to establish a link between mandatory infant restraints on airplanes and increased traffic deaths requires several more inferential steps. Understanding the risks associated with overregulating or not adopting an emerging technology also requires more inferential steps because they come in the form of lost opportunity benefits; lives that could have been saved or improved. On the other hand, the costs associated with adopting an emerging technology are much more visible because they represent a departure from the status quo.

Novelty, media hype, and cost visibility represent only a few of the routes through which the availability heuristic can skew perceptions against an emerging technology in distinct and particularized modes. 30 As shown below, there are numerous other interrelated cognitive biases that affect the availability heuristic and the Precautionary Principle.

D. Informational Access

Decision-makers are only as good as the information they possess. When an emerging technology threatens to disrupt an industry,306 preexisting industry players often face the threat of significant pecuniary losses. 307 Understandably, these self-interested parties respond by discrediting or obstructing the emerging technology. 308 Modern corporate structures and increased fidelity to the shareholder have contributed to this zealous safeguarding of market share and profitability, even at the cost of human life. 309 Some of these defense tactics include the usual and effective lobbying and political spending that influence high level decision-making. 310 However, in a democratic society filled with individual decisionmakers, industry manipulation of the accessibility, pace, and content of information in order to distort public perceptions of risk can be just as effective at preventing market disruption.311

As a general proposition, established market players are likely to react negatively to any developments, tech-related or otherwise, that threaten their bottom lines. The tobacco industry's response to the discovery of a conclusive link between its products and various cancers is a prime example of the depths to which corporations will stoop to protect profitable products. 31 In addition to the typical lobbying and politicking, the tobacco industry engaged in informational warfare on a scale the business world had never seen.313 In response to the carcinogenic discovery, the industry launched a campaign to suppress negative research.3 14 Furthermore, it established a research front in the form of the Tobacco Industry Research Council. 315 "Instead of supporting genuine scientific research into the problems, it spent millions of dollars publicizing research purporting to prove that tobacco did not cause cancer." 3 16 Following decades of misinformation and obfuscation-and unnecessary deaths-public perception of risk eventually caught up with reality.3 1 7 Even still, the industry persisted in its disinformation campaign when the risk posed by second-hand smoke was later revealed. 318 These tactics continue to this day. 319 Importantly, the "industry's strategy does not require winning the debates it manufactures. It is enough to foster and perpetuate the illusion of controversy in order to muddy the waters around scientific findings that threaten the industry." 320 In other words, the mere implantation of a seed of doubt regarding risk levels can be enough to delay accurate public perception of risk by decades. Taking note, other businesses-including fast food restaurants, alcohol producers, and casinos-have launched similar disinformation campaigns with comparable success.32 1

With respect to emerging technologies, the American automobile industry has waged similar disinformation campaigns against new products proven to increase motor vehicle safety. 322 The decades-long battle over seatbelts and airbags represent a paradigmatic example.323 In his revolutionary book, Unsafe at Any Speed, Ralph Nader accused the American auto industry of ignoring technology that increased safety. 324 Worried that an accurate assessment of the risk posed by their cars would hurt their bottom line, the big auto companies fomented disinformation. 325 Like the tobacco industry, the American auto industry established several research and safety foundations whose real purpose was to deflect public risk perception away from dangerous design towards dangerous drivers. 32 They pumped out information claiming consumers did not want increased safety and inaccurate assessments of the costs associated with safety measures.327 They even went as far as to threaten Mr. Nader and dissenting manufacturers who sought to innovate in the field of auto safety. 328 Even after it became clear to the big auto companies that public perception of risk would inevitably catch up with reality, they persisted in publicly stifling safety innovation while privately developing the technology themselves. 329 Following decades of disinformation and unnecessary death, car manufacturers have performed a complete about-face, competing to win the title of safest car on the road.3 30

Another paradigmatic example of information manipulation is the National Football League's ("NFL") suppression of cutting-edge concussion research. 331 Bennet Omalu, portrayed by actor Will Smith in the film Concussion,3 32 famously discovered the neurodegenerative disease chronic traumatic encephalopathy ("CTE")-originally thought to be confined to boxers-in NFL players.33 3 Naively, Dr. Omalu "thought NFL doctors would be pleased when they [learned of his discovery]."3 3 4 However, like the tobacco and auto industries, the NFL had its own counter-research arm, the Mild Traumatic Brain Injury committee.3 Though none of its leading members were neuropathologists, they did their best to discredit Dr. Omalu's work and his reputation. 36 In communications with academics, reporters, and the public, the NFL dismissed his work as "speculative," "flawed," and "not appropriate science."33 7 Moreover, they "'publish[ed] an unprecedented series of papers, several of which were rejected by peer reviewers and editors and later disavowed even by some of their own authors."' 338 Once the NFL realized they could no longer deny the undeniable, they began to suppress the undeniable. 339 A 2016 congressional study accused the NFL of "work[ing] to improperly influence ... government research, trying to steer [a] study toward a doctor with ties to the league. .. .340 After the NFL realized it could not influence the study, it pulled the funds it had promised.34 1 Sadly, while the NFL was busy obfuscating and sowing the seeds of doubt, a generation of young children signed up for youth football completely unaware of just what they were signing up for. 42 Of his groundbreaking research, Dr. Omalu had the following to say: "There are times I wish I never [did it]. It has dragged me into worldly affairs I do not want to be associated with. Human meanness, wickedness, and selfishness. People trying to cover up, to control how information is released."343

Whether motivated by corporate greed, fiduciary duty to the shareholder, or the structure of executive compensation, the ability of industry players to wage informational warfare against emerging technologies has a significant impact on public perception of associated risks. Even giant tech companies that once cut their teeth on innovation are exhibiting similar defensive behaviors. 345 They have been accused of suppressing and stifling emerging technologies by taking advantage of mergers and acquisitions, borderline copyright infringement, and disproportionate economies of scale (e.g., Facebook's strong-armed acquisition346 of Instagram and Amazon's undercutting347 of competitor prices).3 48 Like the tobacco and automotive industries, big tech has also demonstrated a willingness to manipulate the information the public receives. 349 The fact that big tech companies-once themselves champions of disruptive technology-are now themselves stifling innovation lends credence to the notion that emerging technology is particularly susceptible to risk misperception caused by industry manipulation of information.

E. Control

As emerging technology promises to make life increasingly automated, it also becomes exposed to another particularized form of cognitive bias. While much of the fear associated with automation is economic, 350 those fears are inextricably bound to a technophobic fear of losing control.35 1 Fear of losing control, just like any phobia, can inflate a decisionmaker's perception of associated risks. 352

In general, humans experience feelings of anxiety, fear, and helplessness when they perceive a lack of control over their environment.3 5 3 In one study, subjects were more likely to under-perceive the discomfort associated with a painful stimulus when they were provided with illusions of control over that stimulus.354 Those who fear flying consistently rate lack of control as significant source of their phobia.355

In the context of automation and artificial intelligence ("AI"), pop culture hits such as I, Robot, the Matrix, and Stanley Kubrick's cult classic 2001: A Space Odyssey are provocative and arousing precisely because the each tap into a human discomfort with surrendering control to technology. 35 Philosophers have made careers out of proselytizing Singularitarianism, the notion that humans will lose control of Al through an exponentially accelerating chain reaction of machine learning. 357 A simple internet search reveals a plethora of resources aimed at counseling employees through their automation-induced technophobia.358 Intuitively speaking, it is easy to imagine that this anxiety associated with ceding control to automation and artificial intelligence would alter the manner in which humans perceive and interreact with emerging technologies, resulting in a misapplication of the Precautionary Principle against that technology. But it is not just that a fear of losing control influences how a decisionmaker might apply the strong Precautionary Principle. It also influences whether an individual will engage in the fallacy of the strong Precautionary Principle in the first place. 359 Indeed, the paralytic nature of the strong Precautionary Principle itself produces the anxious feeling of losing control.360 Like a cat to a warm beam of sunlight, humans subconsciously seek out comforting illusions of control as a means of cocooning themselves from the realities of indeterminacy. 361 This is part of the reason people engage in irrational hoarding behaviors (e.g., toilet paper shortages as a response to COVID-19) in response to uncontrollable stimuli, such as natural disasters. 36 2 When an analysis under the Precautionary Principle offers no advice because it is paralyzing-as is so often the case with emerging technology-the resulting decisional limbo can produce feelings of anxiety. Because no decision is definitively advised, there is no control to be had. This is a form of cognitive dissonance in which the Precautionary Principle supports both action and inaction.3 4 "The existence of dissonance, being psychologically uncomfortable, motivates the person to reduce the dissonance and leads to avoidance of information likely to increase the dissonance. The greater the magnitude of the dissonance, the greater is the pressure to reduce dissonance." 365 Consequently, in the face of dissonance caused by a paralytic Precautionary Principle, humans, seeking illusions of control, will not only contrive a precautionary answer when the principle offers none, but they will likely choose the option that will itself provide them with the greatest illusion of control. That is, regulation, creating a proverbial double whammy.

F. Age

In general, as humans age they become more risk averse. 36 6 That is, they tend to inflate the risks they perceive. 367 There are numerous reasons for this phenomenon. Some are inherent to aging itself.368 For example, humans generally experience a spike in economic risk aversion around the typical age of retirement, "probably reflect[ing] the shift toward fixed income assets after retirement." 369 Moreover, as physical health and motor function begin to decline, everyday tasks, such as crossing the street or taking a shower, become more risky.370 In that sense, increased risk perception and aversion amongst the elderly are justified by the fact that life does indeed become riskier as one ages. These factors inherent to aging, however, cannot completely account for the drastic increase in risk perception that aging adults often experience. These factors, themselves external to human cognition, nonetheless inform a broader cognitive attitude that the world is riskier than it actually is; particularly so in relation to emerging technology. 371 This is unfortunate considering the fact that emerging technology promises to make life much less risky and much more comfortable and enjoyable for senior citizens.37 2 It is also concerning because the average age of democratic decisionmakers in the U.S. is set to increase as "[t]he aging of baby boomers means that within just a couple decades, older people are projected to outnumber children for the first time in U.S. history." 373

If risk aversion among senior citizens were entirely rational, one would expect a perfect correlation between an increase in an actual aging-related risk and the aversion towards that risk. However, studies measuring increased aversion to non-aging-related risks demonstrate that this phenomenon cannot be explained solely by an actual increase in risks facing the elderly. 374 One such study sought to build upon prior research indicating that information processing speed and other important variables, such as working memory, necessary for complex decision-making deteriorate in humans as they age.37 "[Their] findings confirmed the notion ... that older adults demonstrate risk aversion in the risky choice context in which risk-seeking would be a more effective strategy .. ." as a result of this cognitive decline. 376 One of the ways that older adults subconsciously compensate for this loss in cognition is "through selective engagement in cognitive resources. Older adults may conserve resources ... limiting both the quantity and complexity of the information to which they attend." 377 In other words, older adults possess a generalized aversion to risk.

The implications of this generalized aversion for emerging technology are crystal clear. Analyzing the risks associated with complex emerging technologies requires dedicating a significant amount of cognitive resources towards processing intricate information. 378 As has been explained, understanding the risks associated with a piece of technology is cognitively easier than understanding the substitute costs that regulation would bring about. A generalized risk aversion resulting from a decline in cognitive resources would undoubtedly affect perceptions of emerging technology in a negative manner.

This aversion to risk in general is amplified by a particularized aversion to new technology in older adults. As the brain ages, it becomes less neuroplastic.379 When this occurs, individuals begin to lose the ability to adapt to new stimuli and learn new cognitive and motor skills.380 As the old adage suggests, "you can't teach an old dog new tricks." 38 ' While this is, of course, an overstatement, any child who has had to re-explain how the television remote functions to a parent or grandparent is well-acquainted with this phenomenon. This reduced ability to adapt to new technology results in anxiety, which, in turn, causes a technophobic aversion.382 This irrational phobia serves only to increase the risk aversion older adults feel towards emerging technology, thus inflating perceptions of risk.

IV. THE CONSEQUENCES OF TECHNOLOGICAL RISK MISPERCEPTION

As explained in Part III, technological risk misperception is a distinctive form of misperception because humans are systematically predisposed to overperceiving the risks associated with a new piece of technology. The consequences and costs of technological risk perceptions are also unique because they come in the form of lost benefits and opportunities: lives not saved, lives not improved, profits not made.383 The insidious costs associated with a blind allegiance to the status quo are often not cognitively available to decisionmakers because, as Ike and Tina Turner put it, "you can't miss nothing that you never had." 384

When technological risk misperception leads decisionmakers to shun emerging technology in favor of maintaining the status quo, the world collectively suffers as a result.385 Three contemporary examples of technological risk misperception-drones, self-driving cars, and artificial intelligence-demonstrate the prohibitive yet subtle costs associated with technological risk misperception.

A. The Costs of Fearing Drones

There is no dispute that unmanned aerial vehicles, better known as drones, will revolutionize the human experience for the better.386 They have a proven ability to save lives and deliver necessary goods and services to vulnerable and remote demographics.387 Yet Americans fear them.388 This irrational fear has led to an irrational response. Rather than reflecting a commonsense weighing of the costs and benefits associated with drone technology, the American regulatory response to this promising new technology is a story of systemic risk misperception.389 The result is a reduction of overall social welfare and a stifling of technological advancement. 390

It was not always the case that drone regulation was informed by irrational fear. There was a time when FAA drone "guidelines were lenient, for ... the agency's main purpose was to regulate manned passenger aircraft .... "39 Unfortunately, this "American honeymoon with drone technology" came crashing down in the 2000s when rising public fears put pressure on the FAA to adopt an aggressive regulatory stance. 39 To be sure, drones are a tool capable of abuse just like any other.39 3 In that sense, no one can deny that they do represent a source of risk.394 However, because the FAA's misguided regulations respond to public fears, as opposed to actual risk factors, they accomplish little in the way of mitigation.395

The FAA has issued restrictive commercial drone regulations that have stifled sector growth and pushed innovation abroad.396 The FAA "prohibits commercial drones from flying at nigt, above 400 feet, faster than 100 miles per hour, or over crowds of people." 3 Furthermore, the combined vehicle and cargo weight cannot exceed fifty-five pounds. 398 But the most prohibitive of FAA regulations "provides for 'line of sight' operating requirements .. . [that] eliminate nearly all practical applications of the emerging technology." 399 Lastly, the FAA has implemented registration requirements aimed at deterring criminal uses of drones. 400 The FAA can waive some of the minor regulations; however, these waivers are typically inadequate for most immediate drone applications.40 1

The starting place for any rational discussion of drone regulation is the fact that, in stark contrast to other means of transporting goods and services, there have been zero reported deaths caused by drone related accidents in the United States.4 02 The costly line-of-sight regulation does little to increase public safety. Nominally speaking, it is meant to "reduce collisions by requiring operators to see their drone directly. ... "403 While this requirement might offer some logical appeal to the layman, it is ultimately not grounded in rational thought.4 04 "Drone operation through a live camera feed provides drone operators with a clearer visual of their drones to better see and avoid obstacles in a drone's path." 405 Moreover, advancements in collision-avoidance technology have obviated the need for an operator to keep a drone within his or her visual line of sight.406 In other words, the FAA is trying to address a problem that technology has already solved.

The FAA's registration requirements also miss the mark. As a practical matter, criminals and terrorists are unlikely to register their drones, and the FAA lacks a robust enforcement mechanism to make them do so.4 07 Even worse, in an attempt to deter and catch those few bad actors who would use drone technology to violate the privacy of others, the FAA has created a substitute risk with respect to lawful drone operators. 408 "[I]nformation provided through drone registration will be public, which means names and home addresses of drone pilots-as young as thirteen years old-are public information."4 09 In short, the FAA has exposed lawful operators to the very risk they seek to mitigate with their regulations.

So, why do these ineffective, outmoded regulatory measures persist? The answer is "based [i]n systemic risk-misperception, exaggerating fear over reality."41 0 According to the National Academies of Sciences, Engineering and Medicine, an attitude of zero-tolerance for risk has taken ahold of FAA regulators. 4 1 1 But, as Professor Sunstein has made clear, in a climate of substitute risks and benefits, zero-tolerance is a fallacy.4 12 "It is evident that the FAA's focus concentrates far more on the risks of integrating drones into the national airspace rather than on the benefits that drones provide (or, more importantly, the opportunity costs of not utilizing modern technology)."4 13 Put in more familiar terms, by applying a strong Precautionary Principle to the risks posed by drone implementation, regulators have turned a blind eye towards the benefits and opportunities that have been lost as a result of their decisions.

The costs associated with not innovating in the field of drone technology are massive.4 14 Drones have beneficial applications in a wide array of industries, ranging from medicine to law enforcement and from conservation to tourism.415 Unfortunately, FAA's archaic regulations impede many of these applications. 416 In response, major tech companies are moving their drone programs abroad.417 Google has moved its drone delivery program to Australia. 1 8 Amazon has moved similar programs to Canada and the United Kingdom.4 19 "[T]his lost opportunity means that foreign nations-instead of America-are benefiting from technological advancements, new jobs, and an economic upswing. Foreign nations, "see[ing] an opportunity to capture a market that the FAA is complicit in crippling inside the United States," have moved quickly to clear the way for more drone innovation.42 1

But the costs exacted by technological risk misperception are not limited to economic ones.422 There are direct human costs as well.42 Drone technology has been used in other countries to "deliver emergency equipment and supplies to the world's hard-to-reach areas."4 24 Drones have also been used by search and rescue officials to save lives in remote areas or after natural disasters.4 25 Consequently, thanks to drone technology, deaths that were once tragic are now tragically preventable. "Simply put, the FAA's line-of-sight regulation costs lives. No patient should die because their lifesaving treatment is stuck in traffic.'A 26

Drone regulation in America "is a cautionary tale of how well-intended laws and policies aimed at enhancing safety can silently cost lives rather than protect them."427 It is also a tale of how our brains contribute to systemic risk misperception by amplifying some risks far above reward. Drone regulation underscores the importance of combatting systemic technological risk misperception as well as the tired and fallacious regulatory attitude of better safe than sorry.

B. The Costs of Fearing Autonomous Vehicles

While the previous example largely focused on regulators, the example of autonomous vehicles largely turns on public perceptions of risk, thus highlighting the duality of risk misperception in America. Every three years, as many Americans are killed on the roads "as were killed in all of the country's wars since World War I."428 Consequently, over the course of one's life, driving represents a significant source of risk. Yet Americans do not to treat it that way4'9 Rarely do we stop to consider whether it might be our last day on earth when we start our engines as a police officer might when she starts her day-even though the risk of death is comparable. 430 Some fear flying over driving even though the latter is far more dangerous. 43 1 In short, many Americans downplay the risks associated with driving and underestimate the imperative for a revolution in safety technology. Deaths and injuries on the highways are seen as tragic and unfortunate by the public when they should be viewed as completely preventable. This systemic risk misperception has stalled implementation of the one technology that offers an all-encompassing solution: automation. 432

The human toll associated with maintaining the status quo and failing to develop and implement self-driving cars is staggering.4 33 According to the NHTSA, 36,560 people were killed in traffic crashes in 2018 alone.434 The CDC estimates 2 million more are injured each year.435 The economic costs are also sobering. 436 "[F]or crashes that occurred in 2017, the cost of medical care and productivity losses associated with occupant injuries and deaths from motor vehicle traffic crashes exceeded $75 billion."4 37 Human error is responsible for around ninety percent of all automobile crashes. 438 In other words, drivers as a class represent one of the most dangerous groups in America. Understandably, proponents of self-driving cars seek to remove human error from the equation, much like airplane manufacturers have done with great success. 439

Knowing the high price Americans pay on the roadways each year, one would expect the public to embrace and support any technology that promises to reduce that burden. Sadly, however, motorists have often required convincing before adopting new safety technology.44 0 In the context of automated cars, a major roadblock developers face is convincing motorists to hand the keys over to a computer.441 In one survey of perceived opportunity cost, researchers found that individuals valued time spent in a self-driving Uber as more costly than an identical normal Uber and even more costly than driving themselves.442 This suggests "a lack of familiarity and comfort with driverless technology at present."443

Heuristics and cognitive biases that drive technological risk misperception offer a partial yet substantial explanation for why consumers need convincing. One study of public perceptions of self-driving technology concluded that the "change in status quo-from an active driver to a passive driver-may be perceived as a loss among those who value the feeling of control when driving."444 Reports of individuals sleeping behind the wheel of their Teslas are "disturbing" and "unsettling" precisely because they represent a departure from the familiar status quo to the unfamiliar.44 5 It is worth noting that, despite the salience of these reports, fatalities since Tesla released its autopilot product in 2014 have been exceedingly rare. 44 6 The fear of losing control also helps "explain higher risk and lower benefit perception of self-driving cars."44 7 The study concluded that "[g]iving up control may, in fact, be one of the major barriers to the adoption of self-driving cars."" 8

Unfamiliarity, it seems, is also accompanied by ignorance.449 The same study found "evidence that ... [p]eople who had greater experience with vehicle automation technologies had lower risk and higher benefit perceptions as well as higher trust ratings of self-driving cars .. . ."450 Without this experience and knowledge, individuals rely on their heuristics to fill the decisional void, which typically disfavor emerging technologies. 451 In addition to lack of information there is an issue of disinformation. The publication of rare but retainable negative media hype means that the availability heuristic reinforces already inflated perceptions of risk. Those who had heard stories of accidents involving self-driving cars-such as the tragic and highly-publicized death of a Tempe woman-"reported lower trust levels in self-driving cars."45 2 A single negative story has the power to implant a seed of doubt in the public and derail years of progress. 453

Self-driving cars represent a paradigm of technological risk misperception. Factors inherent in the technology itself and inherent in human behavior operate to inflate risks and obscure benefits.454 While many American drivers are unsure about whether they can ever trust a self-driving car with their family's safety, if they understood their existing vehicle to be the ticking time bomb it represents, they might begin to wonder if they can afford not to.

C. What's Next? The Costs of Fearing Artificial Intelligence

As explained in Section HI.E on losing control, American pop culture has a macabre fascination with artificial intelligence-induced dystopias and doomsdays.455 This is likely because it taps into the powerful human discomfort with losing control. The two preceding examples of systemic technological risk misperception may be harbingers of what is in store for developers of AI. Ironically, one of the most vocal proponents of automated vehicles, Tesla CEO Elon Musk, is also one of the most vocal critics of Al technology.456 He has largely been dismissed by industry insiders as a fear-mongerer, alarmist, and doomsayer. 457 While his "relatively extreme views on AI are shared by a small minority of Al researchers[, his] celebrity status means they're heard by huge audiences and this frustrates people doing actual Al research.' 58

When it comes to Al, Elon Musk is a walking contradiction. On the one hand, he believes that AI development represents possibly the greatest existential threat to human existence.4 59 On the other hand, "Musk's Al investments have allowed him to stay close to the field he's so afraid of."A60 He is automating vehicles, developing neural interfaces, 461 and has profited handsomely off of his AI investments (albeit on the pretense of precaution). 462 On the one hand, Musk thinks there is a good chance we will become slaves to our computers. 63 On the other hand, he thinks there is a "one in billions chance" we are not already living in a simulation designed by a superintelligent entity. 464 It would seem, then, that his fear-mongering is a precaution against a one in billions risk that superintelligence does not already exist.

Whether one understands Elon Musk as a symptom or source of public fears, it is clear that the emerging field of AI technology is at great risk of falling victim to systemic technological risk misperception. In a poll of Americans, fifty-three percent felt advancing the field was important, but the rest felt it was either unnecessary or potentially dangerous. 465 Another survey found that "Americans, on average, expect that high-level machine intelligence will have a harmful impact on balance. Overall, thirty-four percent think that the technology will have a harmful impact; in particular, twelve percent said it could be extremely bad, leading to possible human extinction.466 It seems many Americans are also somewhat uninformed about the wide array of applications and benefits AI technology has to offer. Fifty-three percent said they would use an intelligent robot for dayto-day chores. 46 ' Freeing Americans from their menial tasks represents one of the more inconsequential benefits of Al technology. 68 In response to fearssome rational and some irrational-about the consequences of AI, many are calling for increased regulation of its development. 469 Congress 470 and the White House 471 have expressed interest in responding to these fears. Whether the regulatory response reflects irrational fears, as with drones and self-driving cars, or rational fears, only time will tell. Given AI's potential to completely revolutionize the human experience for the better,472 the lost opportunities that could arise from misperception of the associated risks should give pause to overzealous regulators.