Category Archives: Artificial Intelligence

The cost of AI

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A variant on Moore’s law is the observation that the financial capital required to launch a new business decreases exponentially as technology gets cheaper.

Pre-internet, and using a notional geometric scale for the purposes of illustration, you might have needed $5m to found and build a new venture. The World Wide Web probably reduced that to $500k, while cloud computing brought it down to $50k. With the expansion of SaaS and API solutions, that cost might have been $5k to get going. Now, vibe coding and $500 of AI prompts can probably launch a new website, build a back end database, implement an e-commerce solution and deploy agentic AI bots to go and find your first customers.

This is a great outcome if measured by a lower barrier to market entry. It also enables founders to “fail fast, fail cheap”, and incentivises innovation by financially de-risking the process.

But even though the cost of AI tools is extraordinarily cheap in terms of the computing and processing power they deliver, there is a huge cost to our rapid adoption of AI that needs to be accounted for.

First, we are seeing corporate lay-offs among tech firms and parts of the service industry that no longer need as many human bodies and minds to operate at scale. So there is a human, economic and societal cost of increased un(der)employment.

Second, traditional skills and expertise are being hugely reduced in perceived value – why pay a graphic artist to design an image when I can use dall-e for free?

Third, as more and more creative tasks are being outsourced or delegated to AI (“create a short story about an F1 race in the style of Ernest Hemingway”) we risk losing our own innate creativity (that comes with experimentation, curiosity, play and reflection). This in turn devalues the creative process itself (thanks to cheaper, AI-enabled production).

Fourth, AI (and the Large Language Models on which it is trained) has no great respect for intellectual property. It doesn’t recognise boundaries between copyright material, content that is subject to creative commons, content that is in the public domain, and content which is publicly available. Again, if copyright owners and original content creators are not recognised or compensated for their work, why would anyone aspire to creating anything original?

Finally, there is the cost of resources (energy, water, rare earth metals) needed to maintain huge AI processing plants and data centres. (But at least this demand is accelerating the development of renewable energy.)

A few years ago, I posted a blog about the importance of the human factor, in the face of technological progress brought by automation and AI. I still remain cautiously optimistic that AI will bring huge benefits, despite the rampant growth of AI in the three years since I wrote that piece. But we are currently in an awkward and comfortable transition phase. If more jobs are lost to AI, and if human-led output is increasingly devalued, perhaps we will need to revisit the debate about Universal Basic Income and other policies to facilitate this transition.

Next week: Music, music everywhere…. and none of it very memorable 

More on AI Hallucinations…

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The mainstream adoption of AI continues to reveal the precarious balance between the benefits and the pitfalls.

Yes, AI tools can reduce the time it takes to research information, to draft documents and to complete repetitive tasks.

But, AI is not so good at navigating subtle nuances, interpreting specific context or understanding satire or irony. In short, AI cannot “read the room” based on a few prompts and a collection of databases.

And then there is the issue of copyright licensing and other IP rights associated with the original content that large language models are trained on.

One of the biggest challenges to AI’s credibility is the frequent generation of “hallucinations” – false or misleading results that can populate even the most benign of search queries. I have commented previously on whether these errors are deliberate mistakes, an attempt at risk limitation (disclaimers), or a way of training AI tools on human users. (“Spot the deliberate mistake!) Or a get-out clause if we are stupid enough to rely on a dodgy AI summary!

With the proliferation of AI-generated results (“overviews”) in basic search queries, there is a tendency for AI tools to conflate or synthesize multiple sources and perspectives into a single “true” definition – often without authority or verified citations.

A recent example was a senior criminal barrister in Australia who submitted fake case citations and imaginary speeches in support of a client’s case.

Leaving aside the blatant dereliction of professional standards and the lapse in duty of care towards a client, this example of AI hallucinations within the context of legal proceedings is remarkable on a number of levels.

First, legal documents (statutes, law reports, secondary legislation, precedents, pleadings, contracts, witness statements, court transcripts, etc.) are highly structured and very specific as to their formal citations. (Having obtained an LLB degree, served as a paralegal for 5 years, and worked in legal publishing for more than 10 years, I am very aware of the risks of an incorrect citation or use of an inappropriate decision in support of a legal argument!!!)

Second, the legal profession has traditionally been at the forefront in the adoption and implementation of new technology. Whether this is the early use of on-line searches for case reports, database creation for managing document precedents, the use of practice and case management software, and the development of decision-trees to evaluate the potential success of client pleadings, lawyers have been at the vanguard of these innovations.

Third, a simple document review process (akin to a spell-check) should have exposed the erroneous case citations. The failure to do so reveals a level laziness or disregard that in another profession (e.g., medical, electrical, engineering) could give rise to a claim for negligence. (There are several established resources in this field, so this apparent omission or oversight is frankly embarrassing: https://libraryguides.griffith.edu.au/Law/case-citators, https://guides.sl.nsw.gov.au/case_law/case-citators, https://deakin.libguides.com/case-law/case-citators)

In short, as we continue to rely on AI tools, unless we apply due diligence to these applications or remain vigilant to their fallibility, we use them at our peril.

 

Pop in Perpetuity

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Exactly a year ago, I blogged about ageing rockers and their propensity to continue touring and recording. This past weekend I experienced two events that provided almost polar opposites as to how musicians will perpetuate their “live” legacy. (Of course, in theory, their recordings will last forever, in physical, digital and streaming formats – as long as the equipment, technology and platforms survive…)

On the one hand, there was the Sun Ra Arkestra, who since their founder’s death in 1993, have continued to play the music of Sun Ra, respecting the sound, format and spirit of the original band formed in the 1950s. Some of the current band members played with Sun Ra himself, so there is a thread of continuity that connects us back to the past. But even as these surviving members depart this world, the music of Sun Ra will live on in concert form through subsequent generations of players. This type of perpetuity is not uncommon among bands of the 60s, 70s and 80s, although in many cases, there is usually at least one original band member performing, or members who overlapped with the band founders. (Some notable exceptions: Soft Machine, who continue performing and recording, but whose remaining original member left nearly 50 years ago; and Faust, who split into at least two separate bands that still tour and record under the same name.)

On the other hand, there was the high-tech concert presentation by the late composer and performer Ryuichi Sakamoto, entitled KAGAMI. This involved the use of AR headsets and a 3D avatar of Sakamoto, captured in sound and vision performing a selection of his music, sat at a grand piano. The audience, initially seated in a circle around the virtual performance area in order to acclimatise to what they were seeing, was invited to move around the avatar, and even peer into the open grand piano. Two things were striking: first, the 360 degree image was very impressive in the level of detail; second, even if someone was standing between the viewer and the avatar zone, the headset still presented the image of Sakamoto sat at the keyboard. The technology not only captures a digital visualisation of the pianist in action, it also replicates the notes he played as well as the tonal expression and the timbres, resonances and acoustics of the physical instrument. While the audio HiFi was superior to the atavistic CGI, the latter will no doubt improve; as will the slightly clunky and heavy headsets – the 50 minute duration is probably the most I could have endured.

Neither format of the above concerts is better or superior to the other. Both are authentic in their own way, and true to the artistry of musicians they celebrate. Of course, if we end up using AI to compose “new” music by Sakamoto, that may undermine that authenticity. But given Sun Ra’s origin story, I wouldn’t be surprised if he started beaming his new works from Saturn.

 

A postscript on AI

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AI tools and related search engines should know when a factual reference is incorrect, or indeed whether an individual (especially someone notable) is living or dead. In an interesting postscript to my recent series on AI, I came across this article – written by someone whom Google declared is no longer with us.

Glaring errors like these demand that tech companies (as well as publishers and media outlets who increasingly rely on these tools) take more seriously the individual’s right of reply, the right to correct or amend the record, as well as the right to privacy and to be forgotten on the internet.

As I commented in my series of articles, AI tools such as ChatGPT (and, it seems, Google Search) can easily conflate separate facts into false statements. Another reason to be on our guard as we embrace (and rely on) these new applications.

Next week: Bad Sports