COMMENTARY: By Dr Gavin Ellis

Integrity is the most valued element of a news organisation’s reputation. Without it, it cannot expect its audience to lend credence to what it publishes or broadcasts. So, The New Zealand Herald has dealt itself an awful blow.

Its admission that it used generative AI to scrape content and then create an editorial about the All Blacks came only after it was caught out by Radio New Zealand. RNZ’s subsequent revelation that it may have found another three robot editorials in The Herald was met with sullen silence.

All the country’s largest newspaper will say its that it should have employed more “journalistic rigour”.

That is not good enough. It does not explain why the paper made the bizarre choice to employ Gen AI to create what should be its own opinion. It does not explain why there was no disclosure of its use (although to do so on an editorial should raise more red flags than a North Korean Workers Party anniversary). It does not tell us how widespread the practice is within publications owned by NZME (The Herald editorial was reprinted in its regional titles).

It does not explain why even the most basic subediting was not applied to an obviously deficient piece of writing when editorials have previously been checked and rechecked to prevent the most minor of errors. And it does not reveal what went wrong in the editorial chain of command to allow all or any of the foregoing to occur…or not.

RNZ Mediawatch’s Hayden Donnell did an excellent job in “outing” The Herald’s practice. I admit that when I read the All Blacks editorial my reaction was that it was a particularly badly written leader that had been shoved into the paper unedited. That would have been bad enough, but it never occurred to me that it might be the scribbles of a robot hand.

Donnell had the insight to put it through AI detection software and, like the Customs Service’s First Defender against drugs on Border Patrol, it returned a positive reading. It indicated it was most likely the product of Gen AI. His finding was revealed on Mediawatch last Wednesday. A follow-up fronted by Colin Peacock on Sunday’s Mediawatch revealed a further three editorials — all on sporting subjects — had returned similar readings to the first.

Peacock told listeners the publisher had declined to comment.

AI-created editorials: What in HAL’s name was the Herald thinking?

The Herald’s own disclosure of the issue to its readers was buried in Shayne Currie’s Media Insider column. Headed “AI and that NZ Herald editorial”, it was the fourth item after an interminable piece on TVNZ’s ongoing fight with former Breakfast host Kamahl Santamaria, TVNZ’s CEO paying her own way to the Olympics, and the release of the Wall Street Journal reporter held in Moscow on fabricated charges.

The item about itself assumed everyone had already caught up with the RNZ story and simply began by saying newsroom staff had been called to a meeting “to discuss use of artificial intelligence (AI), following a case in which NZME says it should have applied more “journalistic rigour” in the way AI was used to help create a recent NZ Herald editorial”.

It quoted Herald editor-in-chief (and NZME’s chief content officer-publishing) Murray Kirkness setting out the general principles on which The Herald and other publishers used artificial intelligence. He went on to say:

“I’m keen to hold another of our regular All Hands meetings next week, which will include discussion about our use of AI now and into the future.
“As always, trust and credibility are vitally important to us and will be part of the discussion.
“Next week’s session will be an opportunity for us to talk further about our use of AI and the standards we need to maintain as we use it.”

That does not signal to me — or to other Herald readers — that he accepts there is a major issue facing him and his editorial department. Much as NZME might like to minimise what has happened, this is a serious matter that requires no small amount of damage control.

That daily column headed “We say” is more than just one of the many opinion columns peppered throughout the paper. To my way of thinking, it was supposed to be the considered, intellectually rigorous view of the masthead, one from which the public might form their own opinions and draw their own conclusions.

It was also the place from which the powerful could be called to account. As such it always played a significant role in determining the integrity of the masthead and the trust that readers resided in it. That is why its production each day was the direct responsibility of the editor or deputy editor.

I have been both an editorial writer and an editor. I know, from direct experience, the rigour that must be applied to the processes in its production — from robust discussion of the subject, to determining a justified point of view, and ensuring its accuracy and quality. I have felt the weight of responsibility in its publication each day, a weight that is the greater when calling people to account. Our editorials were unsigned because they represented the view of the masthead. The editor took direct responsibility for what it said.

My mentor, and one of my predecessors as editor of The New Zealand Herald, John Hardingham, wrote in the Manual of Journalism about the delegating nature of the editorial structure. He added the following:

One duty, however, is never delegated. That is the expression of the newspapers’ opinions through its leading articles or editorials. The editor, or the deputy editor, personally chooses the daily topics for comment, defines the approach in consultation with the specialist leader writers, and sub-edits the completed work.

That signalled the significance attached to the editorial column. Even if its readership level is low compared with other parts of the newspaper, that significance is not lost on those in power, and they have learned over time that they ignore editorials at their peril. What is said in the name of the masthead may be the touchpaper that ignites a crowd.

Shayne Currie informed readers on Saturday: “Once upon a time, The Herald had a dedicated team of editorial writers, or at least senior editors who had a special focus to consider the newspaper’s opinion on daily issues. Now, the responsibility falls on a wide cross-section of staff, including journalists who might be specialists in particular areas.”

I sense this is yet another indication of NZME’s laser focus on its digital content. The print edition is a legacy medium which, like a geriatric, is offered palliative services while the real effort is devoted to those with the promise of longer life. The fact the editorial is now written by a “wide cross section” suggests (along with the truncation of letters and addition of forgettable photographs) that the company is unwilling to devote resources to the page that was once the most direct link between paper and public.

That would not be lost on staff who could then be forgiven for regarding the editorial writing assignment as a chore rather than a privilege. Using AI to write the editorial may be a manifestation of that attitude. Sadly, all of this ignores the fact that the editorial also appears in digital form and should be accorded the same status it used to enjoy in print.

Shayne Currie used an unfortunate turn of phrase in the paragraph reproduced above. He said “responsibility falls”. The duty may fall to that wide cross-section but responsibility continues to sit where it has always been — with the person at the top of the editorial tree.

As such it falls to Murray Kirkness to fix what is a deepening problem that has been created not only for The Herald and its fellow NZME publications but for the wider media as well.

The AI generated editorial disclosure is a gift from the gods for those who seek to undermine news media and other institutions. I can hear the repeated refrain: “Don’t believe what they say: It is written by a robot”.

Doubtless, it will be extrapolated to embrace the entire content of the paper: “There aren’t any reporters: It’s written by robots.” Sound implausible? If people believed the claim the country’s reporters and editors had been bribed by the Public Interest Journalism Fund, anything is possible.

The editor-in-chief will have to deal with two related issues.

The first is integrity. I have no doubt that AI can be a useful tool in researching the subject of an editorial but never in writing one. The view of the newspaper must be created by the women and men who know and understand the intrinsic values that cannot be scraped from existing data.

Murray Kirkness must give readers an ironbound guarantee that Gen AI-written editorials have stopped, and will not happen again.

The second is transparency. Artificial intelligence has an undoubted place in the future of journalism where it can have immense benefits in, for example, the “digesting” of vast amounts of data and the processing of information. However, its use must be carefully proscribed by a publicly accessible AI code of conduct, which must also set out standardised forms of guaranteed disclosure of when and how it is employed. Failure to follow the code should be a disciplinary offence that could lead to dismissal.

The Herald must show that it is putting its house in order. It is always ready to hold others accountable. It did so last year over an RNZ staff member’s “Russia-friendly edits” of stories on the war in Ukraine, and did so this year over TVNZ’s missteps with redundancies.

It’s time to hang out its own laundry and show that it intends to be whiter-than-white.

There is a lot riding on the “regular All Hands meeting” at NZME tomorrow. If it minimises or ignores the damage done, it could reap the product of a seed unintentionally sown at the top of the first New Zealand Herald editorial on 13 November 1863. It was a quotation:

“Give every man thy ear, but few thy voice.
Take each man’s censure, but reserve thy judgment.

“This above all: to thine own self be true,
And it must follow, as the night the day,
Thou canst not then be false to any man.”

Sage advice, true, but we should also not lose sight of the fact that the quotation is from Act 1 Scene 3 of Hamlet – one of Shakespeare’s tragedies.

Dr Gavin Ellis holds a PhD in political studies. He is a media consultant and researcher. A former editor-in-chief of The New Zealand Herald, he has a background in journalism and communications — covering both editorial and management roles — that spans more than half a century. Dr Ellis publishes the website knightlyviews.com where this commentary was first published and it is republished by Asia Pacific Report with permission.

This article was first published on Café Pacific.

New Zealand’s Stuff media group has joined other leading news organisations around the world in restricting Open AI from using its content to power artificial intelligence tool Chat GPT.

A growing number of media companies globally have taken action to block access to Open AI bots from crawling and scraping content from their news sites.

Open AI is behind the most well-known and fastest-growing artificial intelligence chatbots, Chat GPT, released late 2022.

“The scraping of any content from Stuff or its news masthead sites for commercial gain has always been against our policy,” says Stuff CEO Laura Maxwell. “But it is important in this new era of Generative AI that we take further steps to protect our intellectual property.”

Generative Artificial Intelligence (Gen AI) is the name given to technologies that use vast amounts of information scraped from the internet to train large language models (LLMs).

This enables them to generate seemingly original answers — in text, visuals or other media — to queries based on mathematically predicting the most likely right answer to a prompt or dialogue.

Some of the most well-known Gen AI tools include Open AI’s ChatGPT and Dall-E, and Google’s Bard.

Surge of unease
There has been a surge of unease from news organisations, artists, writers and other creators of original content that their work has already been harvested without permission, knowledge or compensation by Open AI or other tech companies seeking to build new commercial products through Gen AI technology.

“High quality, accurate and credible journalism is of great value to these businesses, yet the business model of journalism has been significantly weakened as a result of their growth off the back of that work,” said Maxwell.

“The news industry must learn from the mistakes of the past, namely what happened in the era of search engines and social media, where global tech giants were able to build businesses of previously unimaginable scale and influence off the back of the original work of others.

“We recognise the value of our work to Open AI and others, and also the huge risk that these new tools pose to our existence if we do not protect our IP now.”

There is also increasing concern these tools will exacerbate the spread of disinformation and misinformation globally.

“Content produced by journalists here and around the world is the cornerstone of what makes these Gen AI tools valuable to the user,” Maxwell said.

“Without it, the models would be left to train on a sea of dross, misinformation and unverified information on the internet — and increasingly that will become the information that has itself been already generated by AI.

Risk of ‘eating itself’
“There is a risk the whole thing will end up eating itself.”

Stuff and other news companies have been able to block Open AI’s access to their content because its web crawler, GPTBot, is identifiable.

But not all crawlers are clearly labelled.

Stuff has also updated its site terms and conditions to expressly bar the use of its content to train AI models owned by any other company, as well as any other unauthorised use of its content for commercial use.

Earlier this year The Washington Post published a tool that detailed all major New Zealand news websites were already being used by OpenAI.

OpenAI has entered into negotiations with some news organisations in the United States, notably Associated Press, to license their content to train ChatGPT.

So far these agreements have not been widespread although a number of news companies globally are seeking licensing arrangements.

Maxwell said Stuff was looking forward to holding conversations around licensing its content in due course.

Article by AsiaPacificReport.nz

Seeing is no longer believing.

Surprisingly realistic – yet fake – images created by Artificial Intelligence (AI) are here.

To date, most have seemed more like curiosities than genuine deception attempts.

Last month, it was revealed that New Zealand’s National Party had used the AI image generation app Midjourney to produce promotional images. The results included imaginary healthcare workers and fearful-looking citizens worried about crime.

In this case, the use of AI was relatively benign – the AI creations effectively replaced the stock photos that would have been used in the past.

Until a media outlet raised suspicions, few people – if any – had even noticed that the realistic-looking images were actually fake.

While the New Zealand example showed how AI images can be used in election campaigns, we can also expect them to have an outsized impact on international relations.

In March, Bellingcat founder Eliot Higgins tweeted startling ‘deepfake’ images of Donald Trump being ‘arrested’ by New York police.

Higgins, who also used Midjourney, clearly labelled the images as AI creations.

But that did not stop the images from going viral and serving as a showcase of the sophistication of the technology.

Higgins also tweeted fake AI-generated images of an imaginary ‘peace summit’ between Vladimir Putin and Joe Biden – brokered by France’s Emmanuel Macron.

Given the current state of the war in Ukraine, these would be unlikely to fool anyone.

However, the realistic-looking deepfakes Higgins created of an imaginary nuclear explosion in Ukraine showed the potential AI could have amidst the fog of war.

Just after Russia invaded Ukraine last year, a fake video of Volodymyr Zelensky calling on Ukrainians to lay down their arms was published by hackers on the Ukraine 24 news website.

In the Indo-Pacific, it is surely only a matter of time until credible-looking AI-generated images are used to stoke geopolitical tensions in the region even further.

New Zealand Prime Minister Chris Hipkins has echoed his predecessor Jacinda Ardern in decrying what he calls the ‘militarisation of the Pacific’.

But in just the first half of 2023, the US has struck new defence arrangements with the Philippines and Papua New Guinea – a response to China signing its own security pact with Solomon Islands last year.

Tensions are building – and AI could take them to the next level.

Arguably, the sheer vastness of the Pacific creates some advantages for disinformation attempts.

Fake images of, say, military vessels near a remote island atoll could be hard to immediately disprove.

Poor communications infrastructure in the more remote corners of the Pacific will also not help.

Moreover, the rise of AI-created content may mean the public are left wondering what to believe.

A Brookings Institution report published in January identified ‘sowing confusion’ as a major aim of those behind disinformation operations.

The report gives an example of a robotic-like presidential address from Gabon’s president: while some believed it was evidence of a deepfake, others thought the president was simply ill. Regardless of the actual truth, chaos and a military coup attempt ensued.

AI has the power to create a hall of mirrors, where even genuine content is viewed with scepticism and distrust.

A real-life example of AI’s potential to wreak havoc came last month, when a fake image of an explosion at the Pentagon in Washington circulated on Twitter and caused financial markets to tumble briefly.

There are many potential responses to the new AI challenge for international relations.

One option is to regulate.

China recently banned deepfake images of real people unless consent has been given – and the country’s regulator now requires AI-generated, ‘synthetic’ content to be clearly labelled as such.

In New Zealand, the Department of Internal Affairs last week proposed tough new media regulations that would also cover content on social media. The suggestions include ‘warning labels and content advisories’ – and fines for non-compliance.

The downside to regulation is the potential for overreach.

The terms ‘disinformation’ and ‘misinformation’ are now frequently weaponised and used simply to denigrate the arguments of political opponents.

More optimistically, the public are less naïve than they are often given credit for.

After all, most people are by now well-accustomed to the idea that photos can be digitally altered. The first version of what is now Adobe Photoshop was released in 1987.

Still, the need to boost media literacy stood out as a theme in discussions on combating disinformation at the inaugural Global Media Congress that was held in Abu Dhabi last year – a topic that is also likely to feature at the 2023 edition of the event to be held this November.

A new ‘white paper’ from the first Congress, which the author attended as a guest of the organisers, summarised the view that there were no easy quick fixes.

Rather, everyone – from governments, to social media platforms, media outlets, educational institutions and consumers themselves – had a role to play.

Boosting awareness of the potential for AI to be used in disinformation is undoubtedly part of the solution.

We won’t have any choice.

Writing in the Global Media Congress white paper, Copenhagen-based futurist Sofie Hvitved estimates up to 99 per cent of the content we consume in the future could be created by AI.

Beyond this, we probably need to tackle the root causes.

In international relations, the de-escalation of conflicts and tensions would make it much harder for disinformation to take hold.

It is no accident that the current deepfake frontlines are on the battlefields of Ukraine.

In wartime, peacetime rules are thrown out of the window – making almost anything seem possible, or at least potentially plausible.

The fictional nuclear bomb created by Bellingcat’s Eliot Higgins is a prime example.

In the Indo-Pacific, steadily rising geopolitical temperatures form the ideal breeding ground for future AI-generated disinformation and propaganda efforts.

Ultimately, the best recipe to blunt the impact of AI fakes in international relations is as simple as it is difficult.

We need more diplomacy, engagement and compromise between states that don’t see eye-to-eye.

Only by reducing competition and conflict will the terrifying creations of AI seem more like fiction than reality.

Of course, this is easier said than done.

It will take human intervention to solve human problems.

AI can’t do it for us.

Geoffrey Miller is the Democracy Project’s geopolitical analyst and writes on current New Zealand foreign policy and related geopolitical issues. He has lived in Germany and the Middle East and is a learner of Arabic and Russian. Disclosure: Geoffrey attended the Global Media Congress in 2022 as a guest of the organisers, the Emirates News Agency.

Michael Timothy Bennett/Generated using Midjourney, Author provided

To build a machine, one must know what its parts are and how they fit together. To understand the machine, one needs to know what each part does and how it contributes to its function. In other words, one should be able to explain the “mechanics” of how it works.

According to a philosophical approach called mechanism, humans are arguably a type of machine – and our ability to think, speak and understand the world is the result of a mechanical process we don’t understand.

To understand ourselves better, we can try to build machines that mimic our abilities. In doing so, we would have a mechanistic understanding of those machines. And the more of our behaviour the machine exhibits, the closer we might be to having a mechanistic explanation of our own minds.

This is what makes AI interesting from a philosophical point of view. Advanced models such as GPT4 and Midjourney can now mimic human conversation, pass professional exams and generate beautiful pictures with only a few words.

Yet, for all the progress, questions remain unanswered. How can we make something self-aware, or aware that others are aware? What is identity? What is meaning?

Although there are many competing philosophical descriptions of these things, they have all resisted mechanistic explanation.

In a sequence of papers accepted for the 16th Annual Conference in Artificial General Intelligence in Stockholm, I pose a mechanistic explanation for these phenomena. They explain how we may build a machine that’s aware of itself, of others, of itself as perceived by others, and so on.

Read more:
A Google software engineer believes an AI has become sentient. If he’s right, how would we know?

Intelligence and intent

A lot of what we call intelligence boils down to making predictions about the world with incomplete information. The less information a machine needs to make accurate predictions, the more “intelligent” it is.

For any given task, there’s a limit to how much intelligence is actually useful. For example, most adults are smart enough to learn to drive a car, but more intelligence probably won’t make them a better driver.

My papers describe the upper limit of intelligence for a given task, and what is required to build a machine that attains it.

I named the idea Bennett’s Razor, which in non-technical terms is that “explanations should be no more specific than necessary”. This is distinct from the popular interpretation of Ockham’s Razor (and mathematical descriptions thereof), which is a preference for simpler explanations.

The difference is subtle, but significant. In an experiment comparing how much data AI systems need to learn simple maths, the AI that preferred less specific explanations outperformed one preferring simpler explanations by as much as 500%.

Exploring the implications of this discovery led me to a mechanistic explanation of meaning – something called “Gricean pragmatics”. This is a concept in philosophy of language that looks at how meaning is related to intent.

To survive, an animal needs to predict how its environment, including other animals, will act and react. You wouldn’t hesitate to leave a car unattended near a dog, but the same can’t be said of your rump steak lunch.

Being intelligent in a community means being able to infer the intent of others, which stems from their feelings and preferences. If a machine was to attain the upper limit of intelligence for a task that depends on interactions with a human, then it would also have to correctly infer intent.

And if a machine can ascribe intent to the events and experiences befalling it, this raises the question of identity and what it means to be aware of oneself and others.

Causality and identity

I see John wearing a raincoat when it rains. If I force John to wear a raincoat on a sunny day, will that bring rain?

Of course not! To a human, this is obvious. But the subtleties of cause and effect are more difficult to teach a machine (interested readers can check out The Book of Why by Judea Pearl and Dana Mackenzie).

To reason about these things, a machine needs to learn that “I caused it to happen” is different from “I saw it happen”. Typically, we’d program this understanding into it.

However, my work explains how we can build a machine that performs at the upper limit of intelligence for a task. Such a machine must, by definition, correctly identify cause and effect – and therefore also infer causal relations. My papers explore exactly how.

The implications of this are profound. If a machine learns “I caused it to happen”, then it must construct concepts of “I” (an identity for itself) and “it”.

The abilities to infer intent, to learn cause and effect, and to construct abstract identities are all linked. A machine that attains the upper limit of intelligence for a task must exhibit all these abilities.

This machine does not just construct an identity for itself, but for every aspect of every object that helps or hinders its ability to complete the task. It can then use its own preferences as a baseline to predict what others may do. This is similar to how humans tend to ascribe intent to non-human animals.

So what does it mean for AI?

Of course, the human mind is far more than the simple program used to conduct experiments in my research. My work provides a mathematical description of a possible causal pathway to creating a machine that is arguably self-aware. However, the specifics of engineering such a thing are far from solved.

For example, human-like intent would require human-like experiences and feelings, which is a difficult thing to engineer. Furthermore, we can’t easily test for the full richness of human consciousness. Consciousness is a broad and ambiguous concept that encompasses – but should be distinguished from – the more narrow claims above.

I have provided a mechanistic explanation of aspects of consciousness – but this alone does not capture the full richness of consciousness as humans experience it. This is only the beginning, and future research will need to expand on these arguments.

Michael Timothy Bennett does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Can machines be self-aware? New research explains how this could happen – https://theconversation.com/can-machines-be-self-aware-new-research-explains-how-this-could-happen-204371

I wasn’t good at French in my final year of high school. My classmates had five years of language studies behind them. I had three. As a result of my woeful grip on the language, I wrote a terribly bad essay in my final French exam.

The more I read of ChatGPT’s output, the more I am reminded of my final French essay. I could not express the complex ideas I wrote in my English essays, so instead, I repeated the question a lot and clumped together words and phrases that sounded like they kind of went together. There was no logical thread, no cogent argument.

It was a bit like the perplexing, digressive, buzzword-rich oratory stylings of Donald Trump.

I have been a university lecturer, tutor and marker for coming on two decades now and late last year a student submitted an essay that I sent off to the university integrity team, explaining that it was “bad in a new and different way”.

According to Turnitin (our detection software), it wasn’t plagiarised. It didn’t read like it had been written in another language and run through Google Translate. The grammar was impeccable but there were glaring non-sequiturs and it danced around the question, which it repeated several times, but didn’t actually answer.

I didn’t hear back from the integrity people. They probably didn’t know what to do about it and may have been busy, as it was the end of the teaching year. I had also said it wasn’t urgent, as it had failed against my marking key, meaning the student, whose marks had been poor all along, would have to repeat the unit anyway.

New teaching year
A couple of weeks later ChatGPT was made available to the public, joining the dozen or so other AI writers available to people who want AI to string together their sentences.

Now, heading back into a new teaching year, having spent the summer chatting with ChatGPT, I am in conversations with my colleagues about how we should proceed. I teach journalism and my colleagues are from a range of arts and communications disciplines.

Collectively our feelings are mixed, but I’m looking forward to letting my students know about this leap forward in communications technology.

I plan to explain it in the context of the other leaps and lurches I’ve lived through.

This won’t be the first to make swathes of workers redundant. I remember the angst in my industry about digital typesetting usurping the compositors and typesetters, replacing vast numbers of them with far fewer graphic designers.

ChatGPT will undoubtedly take some jobs, but it’s the donkey work of the writing professions. It frees us up to do the innovative fun stuff. Also, while ChatGPT is big and shiny, we’ve known that AI writing is on its way for a long time.

In 2018, Noam Lemelshtrich Latar summed up the progress in our field to date in his book Robot Journalism: Can human journalism survive? He documented the many workplaces already using AI writing software and concluded that there was still work to be done. There still is.

Essay capacity underwhelming
Much of the media racket over ChatGPT this summer has been about its capacity to write essays, and so I have read several essays it has written, and I can happily report that I am underwhelmed by them, but also fascinated by the challenge we face in getting better at describing the ways in which they are bad.

This task is part of the mission humanity more broadly is facing in figuring out what it is that people can do that robots can’t. If robots/AI writers are going to do the donkey-work writing in workplaces, that is not something we need to be training graduates to do.

Graduates need to be able to do things an AI language model can’t, and they need to be able to articulate their skill sets.

So, I will be generating AI content in my classrooms and we are going to set to work pulling it apart, in search of its failings and foibles. We’ll do this together and learn about it and ourselves as we go.

Another big theme in the media hype has been ChatGPT’s ability to “do the marking for us”. This, in my opinion, is rubbish. Sure, you can copy-and-paste some text into ChatGPT and ask it for a comment and a grade, but every university I know of demands more of the markers than a simple comment and grade.

If only it was that simple. But, no. We have to describe the specific criteria every piece of work will be assessed against, and the expectations ascribed to each criterion that will result in the award of a specific number of marks. This forms a table called a rubric, which is embedded in our unit websites and getting the assignments and rubrics out of that software and into ChatGPT would take longer than the tight time allocation we get to mark each piece.

Besides the software we mark in is already replete with time-saving tricks, like a record function so you can speak rather than type feedback and the ability to save commonly used comments.

‘Getting to know students’
In addition, failing to read the assignments would inhibit the “getting to know your students” process that marking their work facilitates, and so I imagine it to be the sort of drain-circling behaviour used by failing teachers on their way out of the profession — as student assessment of teachers who cheat in their marking is going to be on par with teacher assessment of students who cheat in their assessments.

Cheating is a key word here. While ChatGPT is new, universities have longstanding policies and charters that use words like “honesty and fairness” in relation to academic integrity. These are being underscored and highlighted in preparation for the start of semester and hyperlinked to paragraphs about AI writing.

Honest use of ChatGPT will involve disclosure about how it was used, and what measures have been taken to verify its content and iron out its wrinkles. It then joins the swath of online tools we encourage our students to use to prepare them for the professions they’ll enter when they graduate.

For my first year students these will be professions that have adjusted to the existence of AI language models, and so their new graduate brilliance will need to be focused on things only humans can do to make the world a better place. This is how I’m going to frame it in my classes, when our next semester starts.

Dr Kayt Davies is a lecturer in journalism at Curtin University. She is a contributor to Pacific Journalism Review. The article was first published in The West Australian and is republished by Asia Pacific Report with the author’s permission.

Article by AsiaPacificReport.nz

A View from Afar – In this podcast, political scientist Paul Buchanan and Selwyn Manning consider and analyse the most significant global issues that define 2021. The topics include:

– Leadership: Trump, Putin, Xi, Biden,

– Pandemic: Impact of Covid-19 & variants on global security

– Security: Afghanistan, AUKUS, Autonomous Weapons, Cyber-Hackers/Attackers.

You can comment on this debate by clicking on one of these social media channels and interacting in the social media’s comment area. Here are the links:

• Facebook.com/selwyn.manning
• Youtube
• Twitter.com/Selwyn_Manning

If you miss the LIVE Episode, you can see it as video-on-demand, and earlier episodes too, by checking out EveningReport.nz or, subscribe to the Evening Report podcast here.

The MIL Network’s podcast A View from Afar was Nominated as a Top  Defence Security Podcast by Threat.Technology – a London-based cyber security news publication.

Threat.Technology placed A View from Afar at 9th in its 20 Best Defence Security Podcasts of 2021 category. You can follow A View from Afar via our affiliate syndicators.

A View from Afar – In this podcast, political scientist Paul Buchanan and Selwyn Manning will consider and analyse the most significant global issues that define 2021. The topics will include:

– Leadership: Trump, Putin, Xi, Biden,

– Pandemic: Impact of Covid-19 & variants on global security

– Security: Afghanistan, AUKUS, Autonomous Weapons, Cyber-Hackers/Attackers.

Join Paul and Selwyn for this LIVE recording of this podcast while they consider these big issues, and remember any comments you make while live can be included in this programme.

You can comment on this debate by clicking on one of these social media channels and interacting in the social media’s comment area. Here are the links:

• Facebook.com/selwyn.manning
• Youtube
• Twitter.com/Selwyn_Manning

If you miss the LIVE Episode, you can see it as video-on-demand, and earlier episodes too, by checking out EveningReport.nz or, subscribe to the Evening Report podcast here.

The MIL Network’s podcast A View from Afar was Nominated as a Top  Defence Security Podcast by Threat.Technology – a London-based cyber security news publication.

Threat.Technology placed A View from Afar at 9th in its 20 Best Defence Security Podcasts of 2021 category. You can follow A View from Afar via our affiliate syndicators.

A View from Afar – In this podcast, political scientist Paul Buchanan and Selwyn Manning discuss two issues: the evolution of new generation attack drones; and the COP26 meeting in Glasgow this week. Specifically, Buchanan and Manning unpack:

• Whether Geopolitics has railroaded a broad-based consensus of climate interventionism
• Why Russia and China abandoned the Cop26 multilateral forum?
• How mostly developed nations state the take away agreements help address climate change, and how Greenpeace and many other environment groups say fundamental problems remain with how developed nations address the climate change challenge.

ALSO: We discuss the latest in the evolution of high-tech militarised attack drones. What can we now expect to see? And, how will countries defend themselves against AI driven attacks?

You can comment on this debate by clicking on one of these social media channels and interacting in the social media’s comment area. Here are the links:

• Facebook.com/selwyn.manning
• Youtube
• Twitter.com/Selwyn_Manning

If you miss the LIVE Episode, you can see it as video-on-demand, and earlier episodes too, by checking out EveningReport.nz or, subscribe to the Evening Report podcast here.

The MIL Network’s podcast A View from Afar was Nominated as a Top  Defence Security Podcast by Threat.Technology – a London-based cyber security news publication.

Threat.Technology placed A View from Afar at 9th in its 20 Best Defence Security Podcasts of 2021 category. You can follow A View from Afar via our affiliate syndicators.

This 21st century epoch is coming to be one of ‘existential crises’, meaning that various large-scale dangers are increasingly coming to be seen to threaten ‘our’ existence, where ‘our’ most commonly relates to people, but may also relate to multicellular life on Earth. An existential catastrophe might fall short of human extinction; a loss of civilisation would also qualify.

The greatest threats to humanity?

In May on RNZ (Radio New Zealand), Toby Ord discussed a whole range of threats, but emphasised ‘man-made’ threats of human origin over geological and celestial risks such as volcanoes, earthquakes, and asteroids. In his discussion, pandemics were treated as essentially ‘man-made’.

The main existential threats of human origin mentioned were – in no particular order – pandemics, artificial intelligence, climate change, world war, and global poverty. The latter – global poverty – was particularly noted as a problem of ‘moral paralysis’. He believes that “if global poverty was to no longer exist [in the future] at the current levels it was it now, then people would look back and be dumbfounded by the moral paralysis of people”.

While he said, “it was crucial to devote resources to ensure we do not fail the future or past generations”, it is not clear that the form of ‘effective altruism’ that he subscribes to is the answer to the conundrum posed. In our cynical world, we are much better at identifying problems than at actually addressing them.

The Social Dilemma

I watched this Netflix feature documentary about social media and artificial intelligence – The Social Dilemma – a few days ago. The trailer finishes: “If technology creates mass chaos, loneliness, more polarisation, more election hacking, less ability to focus on the real issues, [then] we’re toast. This is checkmate on humanity.”

The existential issue here is the way that, in commercial societies, the mass of people are manipulated (‘influenced’, ‘nudged’) to behave in ways that enable a small elite to successfully pursue the petty yet destructive end of ‘making money’. (In market economies, money works as a ‘means’, not as an ‘end’.) While advertising and other forms of persuasion and guided misinformation have been around for as long as people have existed – and there’s also plenty of deception practiced in nature by other species – the nature of 21st century social media technology makes the processes of manipulation and deception so much faster and more overwhelming. The manipulators now have the means to ‘win’ by creating something akin to a monetary black hole, an outcome that represents the destruction of manipulated and manipulators alike.

This is the ‘artificial intelligence’ variant of the ‘moral paralysis’ problem identified by Ord.

Non-Existence

Of course, to properly understand existence, we have to have some sense of non-existence. Human extinction is no more non-existence than is the death – or non-birth – of an individual person. To appreciate the boundaries of the universe – boundaries in time and space – many of us turn to cosmologists and their astrophysicist colleagues.

On Sunday, RNZ listeners heard astrophysicist Katie Mack discussing cosmic endings, including the eventual fate of the universe. (Interestingly, although the scenarios posited related to billions of years in the future, listeners were engaging from a human-centric viewpoint, pretty much in denial that humans may well be practically extinct by the year 2525, as the famous song goes, long before any cosmic event could possibly affect us.)

The problem with this scientific approach is that it is unable to give any meaning to the concept of ‘non-existence’. We are left to, sort of, imagine a universe that is infinite in both space and time, and also completely empty of mass and energy. But that’s not non-existence.

For non-existence we have to go outside the realm of physical science, and to imagine a ‘being’ that does not exist; an ‘entity’ that does not exist, except, that is, in the imagination of those with a capacity for abstract thought. Such a ‘being’ is of course ‘God’, Who exists only in the non-physical realms of human experience, and Who therefore is not subject to the laws of physical existence. ‘God’ is a very neat and universal solution to the problem of non-existence, and can be applied through literature or mathematics to all aspects of non-existence; not only to the non-existence of the physical universe.

I learned maths before the era of Google. And I was fortunate to have had the same very very good maths teacher from the third form to the fifth form. (I remember him carefully erasing the blackboard of modular arithmetic calculations, so that the next class to use the classroom would not think that he was mad; in one useful version of modular arithmetic, 7+7=2. I also remember learning about Group Theory, and the reaction of one classmate who cried out “What is the use of this?”; and the story told about how the foundations of Group Theory were rapidly scribbled in 1831 by a 20 year old youth – Évariste Galois – who knew he would die in a duel the following morning. That’s a personal existential crisis, if ever there was one.)

As a young man, there were two numbers that particularly fascinated me. One was googol. In those days, ‘googol’ was unambiguously a number, a very big number. The name was coined by a nine-year old, in 1920, so we should actually be celebrating the centenary of googol this year. A googol is 10¹⁰⁰; that is, 1 followed by 100 zeros. Googol took hold of my youthful imagination. (Actually, since then, the number that fascinates me more, today, is 1 googol minus 1. That’s 100 nines; or IG in post-modern Roman Numerals. Quite easy to write, but I challenge anyone to name that number.)

The other number that truly fascinated (and fascinates) me is the number that, for me, best describes God. It is the solution to the simple equation:

•   x²+1 = 0      (alternatively, this means that x is the square root of minus one)

There is no solution. The solution for x does not exist. But, just as the physical universe (universes?) may be best described mathematically as an 11-dimensional multiverse, this little problem of non-existence is not going to get in the way of a creative mathematician. It turns out that, while non-existent, this particular entity is mathematically useful. Just as God is useful enough to have been imagined. The solution to this little algebraic problem is ‘i’, which stands for ‘imaginary number’; it could also stand for ‘abstract intelligence’. Or for God. God is the intelligent construct of the imagination, that enables us to conceive non-existence in a practical and useful way. Practical abstract intelligence, through mathematics and through faith, was the precursor to civilisation.

Our Maker as an Accountant

This brings me to Judith Collins, putative Prime Minister of a National Party led government.

Two weeks ago, she invoked our Maker in an ambiguous political speech, and proceeded over the next few day to reiterate her belief in God – and to pray in view of the television cameras after she voted.

Collins said that a prominent critic of hers “still needs to meet his Maker”. She subsequently explained that we all die one day, and that we all meet our Maker. This idea is an excellent example of the practical utility of God. The idea is that we should live our lives as if – at our ‘end of life’ – we will have to account for our actions and choices. It’s an idea that no doubt helps many of us to lead better – more moral – lives than we otherwise would.

Accountancy is the world’s oldest profession; no other occupation could be called a profession in the absence of an accounting mindframe. So, it is appropriate that our most practical image of God is as an Accountant Creator, deft in the art of existential double-entry bookkeeping. The cosmic Big Bang is most practically thought of as the Creation of the universe from which nothing (literally nothing) became a universe of matter and energy, and a parallel universe of anti-matter and anti-energy. The end of the universe will be when God’s ledger once again balances at zero on both sides.

The universe is a miracle. Indeed, it is good to have political leaders who believe in miracles. And so, each individual life is also a miracle. It is a matter of practical convenience to think of our Maker as also our Accountant (as distinct from our accountant). We are in our Maker’s debt. Should we pay the debt back? Is that what we do when we meet our maker? Or, could we think as a good life as ‘servicing’ our existential debt?

Should we pay the debt forward instead of paying it back? Paying the debt forward would seem to me to be the central concept that underpins the effective altruism which Toby Ord understands as necessary to get us past the year 2525.