Article
Culture
Masculinity
5 min read

Russell Brand and the bystanders: how to say enough is enough

When calling out misogyny, low standards are expected of men. Tiffany Bluhm assesses the ‘Say Maaate’ campaign and explores bystander intervention. Part of the Problem with Men series.

Tiffany Bluhm is a speaker and the author of Prey Tell: Why We Silence Women Who Tell the Truth and How Everyone Can Speak Up. She speaks and writes at the intersection of justice and faith for conferences, churches, and companies.

Three young men sit on a couch. One is leering at a phone while the others look on hesitantly
The 'Say Maaate' interactive video encourages users to pick a moment to act.
Mayor of London.

 In the wake of headlines filling our news feed reporting a story, yet again, of a pop culture icon taking advantage of women, be it Russell Brand or “That 70’s Show” star, Danny Masterson, we’re quick to say “enough is enough,” but perhaps the question to ask is “how do we stop it?” What standards are we expecting of men as individuals and as a collective whole? How will they self-edit their interactions with women? What do we expect of men in the workplace, at the gym, at church, or in the public square? We know what we don’t want them to do, leverage their power, privilege, or platform at a woman’s expense, but that’s an undeniably low bar. What could they do to stop each other before their actions get out of hand? 

Before heinous stories of sexual violence are aired on the BBC or CNN, we’re holding the communal line of what we’ll accept from men. 

After learning of the ‘Say Maaate’ campaign—a public information campaign inviting male mates to call each other out when they witness misogynistic tendencies toward women without jeopardizing the friendship thus jeopardizing the influence on each other—I recognized its brilliance lies in its interception of misconduct before it gains momentum or is considered high stakes. Before heinous stories of sexual violence are aired on the BBC or CNN, we’re holding the communal line of what we’ll accept from men, be it sexist jokes or public harassment. This endeavor, which includes bystander intervention, where those within eyeshot or earshot will attempt to distract and intervene in a potentially hazardous situation when men assert unsolicited dominance or advances toward women, is so successful that it’s employed by the United States military and countless higher education universities and colleges in the States. It puts the onus not on the woman impacted during the encounter, but on those around her, to step up and intervene at the first sign of a power imbalance, ranging from a man standing too close, to a woman darting her eyes to avoid eye contact, to outright sexual and verbal harassment. 

Bystander intervention invites the bystander to disrupt the moment, and after the moment has passed, confront the antagonist with either the benefit of the doubt, “maaate,” if deserving, or a “Man, she didn’t like that, read the room.” Lastly, it beckons the bystander to check on the woman who was the recipient of unwanted harassment. Bystander intervention provides much-needed boundary reminders of what we will and won’t accept in a society where the moral arc of the universe desperately needs to bend toward justice. This practice refuses to normalize women’s subjugation or sexualization, it offers a lifeline where there hasn’t been one before, with women left to their own defences against men with no intention of respecting them.  

I feared the ramifications of speaking up against a man with more clout than I. 

Interestingly, men with power—financial, organizational, political, celebrity—perceive themselves to be more attractive, assume women want them, and sexualize interactions with women. In a world where women are often playing by men’s rules, this makes for disastrous outcomes. Far too many women fear they’ll lose access to their place of perceived or actualized power if they speak up for themselves, or other women, who’ve been maligned, even slightly, by men with power and poor intentions. In my own experience, I feared the ramifications of speaking up against a man with more clout than I. How would this affect my social and professional standing in my community? Would others perceive that I have an axe to grind when that wasn’t the case? Would they frame me as prudish? Would they assume I asked for it? Would they assume I’m trying to unnecessarily take down a “good guy.” Instead of speaking up when the stakes were small, after an off-handed comment, sexist joke, or a lingering hug, I assumed this is just how it is, boys will be boys. If I want to get by in this world, I must put up with it. 

If only the men listening would have thrown him a “maaate.”  

Research shows that this pompous approach men exhibit toward women starts on the playground in primary school, gains steam in the locker room in secondary school, cements itself in university culture, (what Americans refer to as “frat culture”) and before we know it, twentysomething men are carrying this toxic idea of what it means to engage women into adult life, and further, it’s celebrated, as was the case of Brand’s public persona. Too often harassment and misogynistic tendencies of any sort equate to validation of masculinity. In this line of thinking, the subtext is that women exist to be dominated, harassed, or taken advantage of for the sheer pleasure of men. This is the genius of bystander intervention; it swiftly reckons with the subtext of a culture hellbent on letting men get away with whatever they want and whoever they want. 

He addresses her harassers, beckoning them to examine their own lives rather than fixate on hers. 

While the Christian church is no stranger to sexual trysts or infractions by men of the cloth, the ethos of Jesus regards women as worthy not of subjugation nor sexual harassment, but respect and dignified engagement. He modeled this respect and casts a vision for women to find solace and safety in men, never harm. 

A great example of bystander intervention in history starts with pious religious leaders attempting to trap the counter-cultural rabbi Jesus by throwing a woman at his feet, alleging she engaged in adultery, a crime, at the time, worthy of public stoning. A clear imbalance of power, with a woman’s life as collateral for trapping Jesus, the religious leaders wondered if he might keep allegiance to the law or break from it. They made the encounter about Jesus; Jesus centered the encounter on protecting the woman who’d been dragged to the public square. Jesus first intervenes by writing in the sand as his answer to the question posed by the leaders. Her physical safety is of utmost importance as evidenced by his actions. Then, he addresses her harassers, beckoning them to examine their own lives rather than fixate on hers. Finally, he checks in with the undoubtedly traumatized woman, a mere prop in an attempt to trap a man who modeled equality and respect between the sexes. 

If bystander intervention was effective 2,000 years ago to protect and uphold women’s dignity and safety, and has modern success in the military and on university campuses, maybe there’s room for the men in our community to prevent harm before it happens? Maybe we can right cultural wrongs? Maybe before learning of Brand’s misconduct, we’ll learn of a bystander who stepped in before a sexist slur was accepted in everyday conversation or intervened when a woman was uncomfortable. Since the issue is not weak femininity but toxic masculinity, maybe men can learn to say, “Enough is enough.” 

Essay
AI
Culture
9 min read

Here’s why AI needs a theology of tech

As AI takes on tasks once exclusively human, we start to doubt ourselves. We need to set the balance right.

Oliver Dürr is a theologian who explores the impact of technology on humanity and the contours of a hopeful vision for the future. He is an author, speaker, podcaster and features in several documentary films.

In the style of an icon of the Council of Nicea, theologians look on as a cyborg and humanoid AI shake hands
The Council of Nicaeai, reimagined.
Nick Jones/Midjourney.ai

AI is all the rage these days. Researchers branching into natural and engineering sciences are thriving, and novel applications enter the market every week. Pop culture explores various utopian and dystopian future visions. A flood of academic papers, journalistic commentary and essays, fills out the picture.  

Algorithms are at the basis of most activities in the digital world. AI-based systems work at the interface with the analogue world, controlling self-driving cars and robots. They are transforming medical practices - predicting, preventing, diagnosing and supporting therapy. They even support decision-making in social welfare and jurisprudence. In the business sector, they are used to recruit, sell, produce and ship. Much of our infrastructure today crucially depends on algorithms. But while they foster science, research, and innovation, they also enable abuse, targeted surveillance, regulation of access to information, and even active forms of behavioural manipulation. 

The remarkable and seemingly intellectual achievements of AI applications uniquely confront us with our self-understanding as humans: What is there still categorically that distinguishes us from the machines we build? 

In all these areas, AI takes on tasks and functions that were once exclusive to humans. For many, the comparison and competition between humans and (algorithmically driven) machines are obvious. As these lines are written, various applications are flooding the market, characterized by their ‘generative' nature (generative AI). These algorithms, such OpenAI’s the GPT series, go further than anyone expected. Just a few years ago, it was hard to foresee that mindless computational programs could autonomously generate texts that appear meaningful, helpful, and in many ways even ‘human’ to a human conversation partner. Whether those innovations will have positive or negative consequences is still difficult to assess at this point.  

For decades, research has aimed to digitally model human capabilities - our perception, thinking, judging and action - and allow these models to operate autonomously, independent of us. The most successful applications are based on so-called deep learning, a variant of AI that works with neural networks loosely inspired by the functioning of the brain. Technically, these are multilayered networks of simple computational units that collectively encode a potentially highly complex mathematical function.  

You don’t need to understand the details to realize that, fundamentally, these are simple calculations but cleverly interconnected. Thus, deep learning algorithms can identify complex patterns in massive datasets and make predictions. Despite the apparent complexity, no magic is involved here; it is simply applied mathematics. 

Moreover, this architecture requires no ‘mental' qualities except on the part of those who design these programs and those who interpret their outputs. Nevertheless, the achievements of generative AI are astonishing. What makes them intriguing is the fact that their outputs can appear clever and creative – at least if you buy into the rhetoric. Through statistical exploration, processing, and recombination of vast amounts of training data, these systems generate entirely new texts, images and film that humans can interpret meaningfully.  

The remarkable and seemingly intellectual achievements of AI applications uniquely confront us with our self-understanding as humans: Is there still something categorically that distinguishes us from the machines we build? This question arises in the moral vacuum of current anthropology. 

Strictly speaking, only embodied, living and vulnerable humans really have problems that they solve or goals they want to achieve... Computers do not have problems, only unproblematic states they are in. 

The rise of AI comes at a time when we are doubting ourselves. We question our place in the universe, our evolutionary genesis, our psychological depths, and the concrete harm we cause to other humans, animals, and nature as a whole. At the same time, the boundaries between humans and animals and those between humans and machines appear increasingly fuzzy.  

Is the human mind nothing more than the sum of information processing patterns comparable to similar processes in other living beings and in machine algorithms? Enthusiastic contemporaries believe our current AI systems are already worthy of being called ‘conscious’ or even ‘personal beings.’ Traditionally, these would have been attributed to humans exclusively (and in some cases also to higher animals). Our social, political, and legal order, as well as our ethics, are fundamentally based on such distinctions.  

Nevertheless, companies such as OpenAI see in their product GPT-4 the spark of ‘artificial general intelligence,’ a form of intelligence comparable to or even surpassing humans. Of course, such statements are part of an elaborate marketing strategy. This tradition dates to John McCarthy, who coined the term “AI” and deliberately chose this over other, more appropriate, descriptions like “complex information processing” primarily because it sounded more fundable. 

Such pragmatic reasons ultimately lead to an imprecise use of ambiguous terms, such as ‘intelligence.’ If both humans and machines are indiscriminately called ‘intelligent,’ this generates confusion. Whether algorithms can sensibly be called ‘intelligent’ depends on whether this term refers to the ability to perform simple calculations, process data, the more abstract ability to solve problems, or even the insightful understanding (in the sense of Latin intellectus) that we typically attribute only to the embodied reason of humans.  

However, this nuanced view of ‘intelligence’ was given up under the auspices of the quest for an objectively scientific understanding of the subject. New approaches deliberately exclude the question of what intelligence is and limit themselves to precisely describing how these processes operate and function.  

Current deep learning algorithms have become so intricate and complex that we can’t always understand how they arrive at their results. These algorithms are transparent but not in how they reach a specific conclusion; hence, they are also referred to as black-box algorithms. Some strands in the cognitive sciences understand the human mind as a kind of software running on the hardware of the body. If that were the case, the mind could be explained through the description of brain states, just like the software on our computers.  

However, these paradigms are questionable. They cannot explain what it feels like to be a conscious person, to desire things, be abhorred by other things and to understand when something is meaningful and significant. They have no grasp on human freedom and the weight of responsibility that comes with leading a life. All of these human capacities require, among other things, an understanding of the world, that cannot be fully captured in words and that cannot be framed as a mathematical function.  

There are academic studies exploring the conception of embodied, embedded, enactive, and extended cognition, which offer a more promising direction. Such approaches explore the role of the body and the environment for intelligence and cognitive performance, incorporating insights from philosophy, psychology, biology, and robotics. These approaches think about the role our body as a living organism plays in our capacity to experience, think and live with others. AI has no need for such a living body. This is a categorical difference between human cognition and AI applications – and it is currently not foreseeable that those could be levelled (at least not with current AI architectures). Therefore, in the strictest sense, we cannot really call our algorithms ‘intelligent' unless we explicitly think of this as a metaphor. AI can only be called 'intelligent' metaphorically because these applications do not 'understand' the texts they generate, and those results do not mean anything to them. Their results are not based on genuine insight or purposes for the world in which you and I live. Rather they are generated purely based on statistical probabilities and data-based predictions. At most, they operate with the human intelligence that is buried in the underlying training data (which human beings have generated).  

However, all of this generated material has meaning and validity only for embodied humans. Strictly speaking, only embodied, living and vulnerable humans really have problems that they solve or goals they want to achieve (with, for example, the help of data-based algorithms). Computers do not have problems, only unproblematic states they are in. Therefore, algorithms appear 'intelligent' only in contexts where we solve problems through them. 

 When we do something with technology, technology always also does something to us. 

AI does not possess intrinsic intelligence and simulates it only due to human causation. Therefore, it would be more appropriate to speak of ‘extended intelligence': algorithms are not intelligent in themselves, but within the framework of human-machine systems, they represent an extension of human intelligence. Or even better would be to go back behind McCarthy and talk about 'complex information processing.’ 

Certainly, such a view is still controversial today. There are many philosophical, economic, and socio-political incentives to attribute human qualities to algorithms and, at the same time, to view humans as nothing more than biological computers. Such a view already shapes the design of our digital future in many places. Putting it bluntly, calling technology ‘intelligent’ makes money. 

What would an alternative, more holistic view of the future look like that took the makeup of humanity seriously?  

A theology of technology (Techniktheologie) tackles this question, ultimately placing it in the horizon of belief in God. However, it begins by asking how technology can be integrated into our lives in such a way that it empowers us to do what we truly want and what makes life better. Such an approach is neither for or against technology but rather sober and critical in the analytical sense. Answering those questions requires a realistic understanding of humans, technology, and their various entanglements, as well as the agreement of plural societies on the goals and values that make a good life.  

When we do something with technology, technology always also does something to us. Technology is formative, meaning it changes our experience, perception, imagination, and thus also our self-image and the future we can envision. AI is one of the best examples of this: designing AI is designing how people can interact with a system, and that means designing how they will have to adapt to it. Humans and technology cannot be truly isolated from each other. Technology is simply part of the human way of life.  

And yet, we also need to distinguish humans from technology despite all the entanglements: humans are embodied, rational, free, and endowed with incomparable dignity as images of God, capable of sharing values and articulating goals on the basis of a common (human) way of life. Even the most sophisticated deep learning applications are none of these. Only we humans live in a world where responsibility, sin, brokenness, and redemption matter. Therefore it is up to us to agree on how we want to shape the technologized future and what values should guide us on this path.  

Here is what theology can offer the development of technology. Theology addresses the question of the possible integration of technology into the horizon of a good life. Any realistic answer to this question must combine an enlightened understanding of technology with a sober view of humanity – seeing both human creative potential and their sinfulness and brokenness. Only through and with humans will our AI innovations genuinely serve the common good and, thus, a better future for all.  

 

Find out more about this topic: Assessing deep learning: a work program for the humanities in the age of artificial intelligence