Governments and companies often use consent to justify the use of facial recognition technologies for surveillance. Many proposals for regulating facial recognition technology incorporate consent rules as a way to protect those faces that are being tagged and tracked. But consent is a broken regulatory mechanism for facial surveillance. The individual risks of facial surveillance are impossibly opaque, and our collective autonomy and obscurity interests aren’t captured or served by individual decisions.
In this article, we argue that facial recognition technologies have a massive and likely fatal consent problem. We reconstruct some of Nancy Kim’s fundamental claims in Consentability: Consent and Its Limits, emphasizing how her consentability framework grants foundational priority to individual and social autonomy, integrates empirical insights into cognitive limitations that significantly impact the quality of human decision-making when granting consent, and identifies social, psychological, and legal impediments that allow the pace and negative consequences of innovation to outstrip the protections of legal regulation.
We also expand upon Kim’s analysis by arguing that valid consent cannot be given for face surveillance. Even if valid individual consent to face surveillance was possible, permission for such surveillance is in irresolvable conflict with our collective autonomy and obscurity interests. Additionally, there is good reason to be skeptical of consent as the justification for any use of facial recognition technology, including facial characterization, verification, and identification.
'Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements' by Lisa Feldman Barrett, Ralph Adolphs, Stacy Marsella, Aleix M. Martinez and Seth D Pollak in (2019) 20(1) Psychological Science in the Public Interest comments
It is commonly assumed that a person’s emotional state can be readily inferred from his or her facial movements, typically called emotional expressions or facial expressions. This assumption influences legal judgments, policy decisions, national security protocols, and educational practices; guides the diagnosis and treatment of psychiatric illness, as well as the development of commercial applications; and pervades everyday social interactions as well as research in other scientific fields such as artificial intelligence, neuroscience, and computer vision. In this article, we survey examples of this widespread assumption, which we refer to as the common view, and we then examine the scientific evidence that tests this view, focusing on the six most popular emotion categories used by consumers of emotion research: anger, disgust, fear, happiness, sadness, and surprise. The available scientific evidence suggests that people do sometimes smile when happy, frown when sad, scowl when angry, and so on, as proposed by the common view, more than what would be expected by chance. Yet how people communicate anger, disgust, fear, happiness, sadness, and surprise varies substantially across cultures, situations, and even across people within a single situation. Furthermore, similar configurations of facial movements variably express instances of more than one emotion category. In fact, a given configuration of facial movements, such as a scowl, often communicates something other than an emotional state. Scientists agree that facial movements convey a range of information and are important for social communication, emotional or otherwise. But our review suggests an urgent need for research that examines how people actually move their faces to express emotions and other social information in the variety of contexts that make up everyday life, as well as careful study of the mechanisms by which people perceive instances of emotion in one another. We make specific research recommendations that will yield a more valid picture of how people move their faces to express emotions and how they infer emotional meaning from facial movements in situations of everyday life. This research is crucial to provide consumers of emotion research with the translational information they require.
The authors argue
Faces are a ubiquitous part of everyday life for humans. People greet each other with smiles or nods. They have face-to-face conversations on a daily basis, whether in person or via computers. They capture faces with smartphones and tablets, exchanging photos of themselves and of each other on Instagram, Snapchat, and other social-media platforms. The ability to perceive faces is one of the first capacities to emerge after birth: An infant begins to perceive faces within the first few days of life, equipped with a preference for face-like arrangements that allows the brain to wire itself, with experience, to become expert at perceiving faces (Arcaro, Schade, Vincent, Ponce, & Livingstone, 2017; Cassia, Turati, & Simion, 2004; Gandhi, Singh, Swami, Ganesh, & Sinhaet, 2017; Grossmann, 2015; L. B. Smith, Jayaraman, Clerkin, & Yu, 2018; Turati, 2004; but see Young and Burton, 2018, for a more qualified claim). Faces offer a rich, salient source of information for navigating the social world: They play a role in deciding whom to love, whom to trust, whom to help, and who is found guilty of a crime (Todorov, 2017; Zebrowitz, 1997, 2017; Zhang, Chen, & Yang, 2018).
Beginning with the ancient Greeks (Aristotle, in the 4th century BCE) and Romans (Cicero), various cultures have viewed the human face as a window on the mind. But to what extent can a raised eyebrow, a curled lip, or a narrowed eye reveal what someone is thinking or feeling, allowing a perceiver’s brain to guess what that someone will do next? The answers to these questions have major consequences for human outcomes as they unfold in the living room, the classroom, the courtroom, and even on the battlefield. They also powerfully shape the direction of research in a broad array of scientific fields, from basic neuroscience to psychiatry.
Understanding what facial movements might reveal about a person’s emotions is made more urgent by the fact that many people believe they already know. Specific configurations of facial-muscle movements appear as if they summarily broadcast or display a person’s emotions, which is why they are routinely referred to as emotional expressions and facial expressions. A simple Google search for the phrase “emotional facial expressions” (see Box 1 in the Supplemental Material available online) reveals the ubiquity with which, at least in certain parts of the world, people believe that certain emotion categories are reliably signaled or revealed by certain facial-muscle movement configurations—a set of beliefs we refer to as the common view (also called the classical view; L. F. Barrett, 2017b). Likewise, many cultural products testify to the common view. Here are several examples:
- Technology companies are investing tremendous resources to figure out how to objectively “read” emotions in people by detecting their presumed facial expressions, such as scowling faces, frowning faces, and smiling faces, in an automated fashion. Several companies claim to have already done it (e.g., Affectiva.com, 2018; Microsoft Azure, 2018). For example, Microsoft’s Emotion API promises to take video images of a person’s face to detect what that individual is feeling. Microsoft’s website states that its software “integrates emotion recognition, returning the confidence across a set of emotions . . . such as anger, contempt, disgust, fear, happiness, neutral, sadness, and surprise. These emotions are understood to be cross-culturally and universally communicated with particular facial expressions” (screen 3).
- Countless electronic messages are annotated with emojis or emoticons that are schematized versions of the proposed facial expressions for various emotion categories (Emojipedia.org, 2019).
- Putative emotional expressions are taught to preschool children by displaying scowling faces, frowning faces, smiling faces, and so on, in posters (e.g., use “feeling chart for children” in a Google image search), games (e.g., Miniland emotion games; Miniland Group, 2019), books (e.g., Cain, 2000; T. Parr, 2005), and episodes of Sesame Street (among many examples, see Morenoff, 2014; Pliskin, 2015; Valentine & Lehmann, 2015).
- Television shows (e.g., Lie to Me; Baum & Grazer, 2009), movies (e.g., Inside Out; Docter, Del Carmen, LeFauve, Cooley, and Lassetter, 2015), and documentaries (e.g., The Human Face, produced by the British Broadcasting Company; Cleese, Erskine, & Stewart, 2001) customarily depict certain facial configurations as universal expressions of emotions.
- Magazine and newspaper articles routinely feature stories in kind: facial configurations depicting a scowl are referred to as “expressions of anger,” facial configurations depicting a smile are referred to as “expressions of happiness,” facial configurations depicting a frown are referred to as “expressions of sadness,” and so on.
- Agents of the U.S. Federal Bureau of Investigation (FBI) and the Transportation Security Administration (TSA) were trained to detect emotions and other intentions using these facial configurations, with the goal of identifying and thwarting terrorists (R. Heilig, special agent with the FBI, personal communication, December 15, 2014; L. F. Barrett, 2017c).
- The facial configurations that supposedly diagnose emotional states also figure prominently in the diagnosis and treatment of psychiatric disorders. One of the most widely used tasks in autism research, the Reading the Mind in the Eyes Test, asks test takers to match photos of the upper (eye) region of a posed facial configuration with specific mental state words, including emotion words (Baron-Cohen, Wheelwright, Hill, Raste, & Plumb, 2001). Treatment plans for people living with autism and other brain disorders often include learning to recognize these facial configurations as emotional expressions (Baron-Cohen, Golan, Wheelwright, & Hill, 2004; Kouo & Egel, 2016). This training does not generalize well to real-world skills, however (Berggren et al., 2018; Kouo & Egel, 2016).
- “Reading” the emotions of a defendant — in the words of Supreme Court Justice Anthony Kennedy, to “know the heart and mind of the offender” (Riggins v. Nevada, 1992, p. 142) — is one pillar of a fair trial in the U.S. legal system and in many legal systems in the Western world. Legal actors such as jurors and judges routinely rely on facial movements to determine the guilt and remorse of a defendant (e.g., Bandes, 2014; Zebrowitz, 1997). For example, defendants who are perceived as untrustworthy receive harsher sentences than they otherwise would (J. P. Wilson & Rule, 2015, 2016), and such perceptions are more likely when a person appears to be angry (i.e., the person’s facial structure looks similar to the hypothesized facial expression of anger, which is a scowl; Todorov, 2017).
An incorrect inference about defendants’ emotional state can cost them their children, their freedom, or even their lives (for recent examples, see L. F. Barrett, 2017b, beginning on page 183).
But can a person’s emotional state be reasonably inferred from that person’s facial movements? In this article, we offer a systematic review of the evidence, testing the common view that instances of an emotion category are signaled with a distinctive configuration of facial movements that has enough reliability and specificity to serve as a diagnostic marker of those instances. We focus our review on evidence pertaining to six emotion categories that have received the lion’s share of attention in scientific research—anger, disgust, fear, happiness, sadness, and surprise—and that, correspondingly, are the focus of the common view (as evidenced by our Google search, summarized in Box 1 in the Supplemental Material). Our conclusions apply, however, to all emotion categories that have thus far been scientifically studied. We open the article with a brief discussion of its scope, approach, and intended audience. We then summarize evidence on how people actually move their faces during episodes of emotion, referred to as studies of expression production, following which we examine evidence on which emotions are actually inferred from looking at facial movements, referred to as studies of emotion perception. We identify three key shortcomings in the scientific research that have contributed to a general misunderstanding about how emotions are expressed and perceived in facial movements and that limit the translation of this scientific evidence for other uses:
- Limited reliability (i.e., instances of the same emotion category are neither reliably expressed through nor perceived from a common set of facial movements).
- Lack of specificity (i.e., there is no unique mapping between a configuration of facial movements and instances of an emotion category).
- Limited generalizability (i.e., the effects of context and culture have not been sufficiently documented and accounted for).
We then discuss our conclusions, followed by proposals for consumers on how they might use the existing scientific literature. We also provide recommendations for future research on emotion production and perception with consumers of that research in mind. We have included additional detail on some topics of import or interest in the Supplemental Material.
