Review
Books
Culture
4 min read

Remembering red on red

The cultural revolution's factions have a disconcertingly contemporary feel.

Simon is Bishop of Tonbridge in the Diocese of Rochester. He writes regularly round social, cultural and political issues.

A Chinese stamp depicts a map of the country from which people march holding a little red book
Long Live the Overall Victory of the Great Proletarian Cultural Revolution, stamp, 1968.
Public domain, via Wikimedia.

Modern era China has suffered human loss on an unimaginable scale.  The Taiping Rebellion in the mid-nineteenth century cost over 20 million lives, more or less the global total from the Great War of 1914-18.  The vicious Japanese occupation in the 1930s led to 15 million Chinese deaths.  The famine begun in 1958, precipitated by the Great Leap Forward, caused around 40 million deaths.   

For one nation, however large, these are appalling losses.  By contrast, the fatalities in the Cultural Revolution (1966-1976) amounted to one million or more.  But the impact of this communist insurgency within a communist state is profoundly felt today, for its generation is still alive.  The trauma of those years has wounded the bodies and minds of millions; people who are unsure how to come to terms with it because of the uncertainty of what can be safely talked about.   

Mao’s incitement to younger people to turn on their teachers and elders in vitriolic criticism and violent attack, including torture and murder, was an attempt to re-boot the revolution by exterminating elements of western capitalism and traditional Chinese authority – the so-called Four Olds of ideas, culture, customs and habits.  The humiliation of teachers and parents was profoundly at odds with the Confucian culture of respect for elders, and it was embedded in young minds whose frontal lobes had not fully developed and where empathy was unformed.  The ensuing violence, pain and hardship was sickening, encompassing millions. 

Many of the bereaved and injured, the perpetrators and the victims, are still alive.  Some bury their memories as a way of coping; others search for meaning, but run up against an authoritarian government with new digital tools that make totalitarianism possible.  In her book Red Memory (Faber and Faber, 2024), Tania Branigan has produced a masterpiece of literature.  Interviewing survivors, bystanders and instigators of the violence, she has produced a history of their guilt and trauma, while reflecting on the uses of memory.   

The collateral from this is human rights abuses on an industrial scale, to ensure there is no opposition to the CCP as the true expression of being Chinese.   

The word remember is coded with meaning.  When we piece together our memories of the past, we re-member them and the members are frequently not put back together again in the way an event happened.  This becomes more pronounced with the passage of time and the known tendency for people to make themselves more central to a story than they were at the time.  We also narrate the past in ways that burnish our reputation and preserve our conscience.  The Cultural Revolution has been reassembled in fragments; there is, and there will be, no initiative like South Africa’s Truth and Reconciliation Commission.  People can make of it what they want; but without justice, the losses fester. 

The lack of a shared public memory also means the Cultural Revolution can be made to service any goal.  Detached from the moorings of truth, it becomes a malleable symbol.  Xi Jinping suffered himself.  His father was purged, denounced as a counter-revolutionary, and sent to hard work in rural Shaanxi Province.  This is his creation myth, and how it made a man out of him.  But there are other lessons to be taken from that time which he has strategically and wilfully ignored.  The leaders of the Chinese Communist Party (CCP) who followed Mao were determined that never again would one man develop a cult of personality like his, by ensuring limited presidential terms.  Xi Jinping has abolished this limit and introduced Xi Jinping Thought in an echo of Mao’s Little Red Book.  If there is one thing Xi has taken from his experience, it is the terror that chaos unleashes and the need to avoid it at all costs.  The collateral from this is human rights abuses on an industrial scale, to ensure there is no opposition to the CCP as the true expression of being Chinese.

Idolatry is much harder to identify in our own culture, yet it is here we need to do this work

The cult of Mao was idolatrous, usurping Christ.  Jesus said he would divide families: ‘father against son…mother against daughter…mother-in-law against her daughter-in-law’.  This divisiveness was located in his claim to be the way, the truth and the life.  He did not seek to divide families, but knew his claims would do so.  Mao intentionally turned families against themselves - the foundation of a civil society - to ensure loyalty to him would not be compromised.          

It is easy to identify this several decades on and at the safe distance of several thousand miles.  Idolatry is much harder to identify in our own culture, yet it is here we need to do this work.  It is also sloppy to make links between the ideological fervour and purity of Maoism and today’s social media culture.  There is no direct link, despite some claims.  But the story of how groups coalesce righteously and are manipulated into ever more extreme forms of factional purity has a disconcertingly contemporary feel. 

Article
AI
Culture
Generosity
Psychology
Virtues
5 min read

AI will never codify the unruly instructions that make us human

The many exceptions to the rules are what make us human.
A desperate man wearing 18th century clothes holds candlesticks
Jean Valjean and the candlesticks, in Les Misérables.

On average, students with surnames beginning in the letters A-E get higher grades than those who come later in the alphabet. Good looking people get more favourable divorce settlements through the courts, and higher payouts for damages. Tall people are more likely to get promoted than their shorter colleagues, and judges give out harsher sentences just before lunch. It is clear that human judgement is problematically biased – sometimes with significant consequences. 

But imagine you were on the receiving end of such treatment, and wanted to appeal your overly harsh sentence, your unfair court settlement or your punitive essay grade: is Artificial Intelligence the answer? Is AI intelligent enough to review the evidence, consider the rules, ignore human vagaries, and issue an impartial, more sophisticated outcome?  

In many cases, the short answer is yes. Conveniently, AI can review 50 CVs, conduct 50 “chatbot” style interviews, and identify which candidates best fit the criteria for promotion. But is the short and convenient answer always what we want? In their recent publication, As If Human: Ethics and Artificial Intelligence, Nigel Shadbolt and Roger Hampson discuss research which shows that, if wrongly condemned to be shot by a military court but given one last appeal, most people would prefer to appeal in person to a human judge than have the facts of their case reviewed by an AI computer. Likewise, terminally ill patients indicate a preference for doctor’s opinions over computer calculations on when to withdraw life sustaining treatment, even though a computer has a higher predictive power to judge when someone’s life might be coming to an end. This preference may seem counterintuitive, but apparently the cold impartiality—and at times, the impenetrability—of machine logic might work for promotions, but fails to satisfy the desire for human dignity when it comes to matters of life and death.  

In addition, Shadbolt and Hampson make the point that AI is actually much less intelligent than many of us tend to think. An AI machine can be instructed to apply certain rules to decision making and can apply those rules even in quite complex situations, but the determination of those rules can only happen in one of two ways: either the rules must be invented or predetermined by whoever programmes the machine, or the rules must be observable to a “Large Language Model” AI when it scrapes the internet to observe common and typical aspects of human behaviour.  

The former option, deciding the rules in advance, is by no means straightforward. Humans abide by a complex web of intersecting ethical codes, often slipping seamlessly between utilitarianism (what achieves the most amount of good for the most amount of people?) virtue ethics (what makes me a good person?) and theological or deontological ideas (what does God or wider society expect me to do?) This complexity, as Shadbolt and Hampson observe, means that: 

“Contemporary intellectual discourse has not even the beginnings of an agreed universal basis for notions of good and evil, or right and wrong.”  

The solution might be option two – to ask AI to do a data scrape of human behaviour and use its superior processing power to determine if there actually is some sort of universal basis to our ethical codes, perhaps one that humanity hasn’t noticed yet. For example, you might instruct a large language model AI to find 1,000,000 instances of a particular pro-social act, such as generous giving, and from that to determine a universal set of rules for what counts as generosity. This is an experiment that has not yet been done, probably because it is unlikely to yield satisfactory results. After all, what is real generosity? Isn’t the truly generous person one who makes a generous gesture even when it is not socially appropriate to do so? The rule of real generosity is that it breaks the rules.  

Generosity is not the only human virtue which defies being codified – mercy falls at exactly the same hurdle. AI can never learn to be merciful, because showing mercy involves breaking a rule without having a different rule or sufficient cause to tell it to do so. Stealing is wrong, this is a rule we almost all learn from childhood. But in the famous opening to Les Misérables, Jean Valjean, a destitute convict, steals some silverware from Bishop Myriel who has provided him with hospitality. Valjean is soon caught by the police and faces a lifetime of imprisonment and forced labour for his crime. Yet the Bishop shows him mercy, falsely informing the police that the silverware was a gift and even adding two further candlesticks to the swag. Stealing is, objectively, still wrong, but the rule is temporarily suspended, or superseded, by the bishop’s wholly unruly act of mercy.   

Teaching his followers one day, Jesus stunned the crowd with a catalogue of unruly instructions. He said, “Give to everyone who asks of you,” and “Love your enemies” and “Do good to those who hate you.” The Gospel writers record that the crowd were amazed, astonished, even panicked! These were rules that challenged many assumptions about the “right” way to live – many of the social and religious “rules” of the day. And Jesus modelled this unruly way of life too – actively healing people on the designated day of rest, dining with social outcasts and having contact with those who had “unclean” illnesses such as leprosy. Overall, the message of Jesus was loud and clear, people matter more than rules.  

AI will never understand this, because to an AI people don’t actually exist, only rules exist. Rules can be programmed in manually or extracted from a data scrape, and one rule can be superseded by another rule, but beyond that a rule can never just be illogically or irrationally broken by a machine. Put more simply, AI can show us in a simplistic way what fairness ought to look like and can protect a judge from being punitive just because they are a bit hungry. There are many positive applications to the use of AI in overcoming humanity’s unconscious and illogical biases. But at the end of the day, only a human can look Jean Valjean in the eye and say, “Here, take these candlesticks too.”   

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