Category Archives: Intellectual Property Rights

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.

 

Pudgy Penguins come to Melbourne

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Last week, I got to chill out with some of the Pudgy Penguins crew, as they launched the Oceania chapter of their NFT community. In case you weren’t aware, Pudgy Penguins are one of the top NFT collections, and have built a loyal fan base for these digital characters.

I went to a major Pudgy Penguin “Pengu Fest” in Hong Kong last year, and got to see first hand how engaged their members are. I also gained some insights as to how this ecosystem enables their NFT holders to license the IP associated with their individual characters into royalty-based income. In short, a subset of the NFT characters are chosen to be turned into merchandise. (For example, Pudgy Penguin soft toys are available in major stores such as Walmart in the USA, and Big W in Australia.) Owners of the selected NFTs earn a percentage of the sales revenue (less tax and production costs etc.).

The most recent collection of Pudgy collectibles are the Igloo figurines, which include early online access to Pudgy World. As a proud owner of one of these plastic figures, I’m still not sure what I have let myself in for…

As well as local meetups, other ways in which the community can interact include a trading card game called Vibes, also launched via the Overpass IP licensing platform.

Igloo Inc, the parent company to Pudgy Penguins and Overpass, has also announced it is launching a Layer 2 blockchain on Ethereum, to be called Abstract, and is being positioned as a “the blockchain for consumer crypto”.

Whatever your views on crypto, NFTs, on-line worlds and collectibles, there is no doubt that Pudgy Penguins have set themselves up with the admirable goals of building a healthy and inclusive community, underpinned by the twin pillars of individual creativity and positive culture.

To crypto sceptics (and the merely crypto curious), the “community” and the enthusiasm of its members could resemble something of a cult. Someone did say during last week’s panel discussion that “I am my penguin, and my penguin is me”. But there are worse things for people to get involved with – and for younger people (I don’t regard myself as part of the Pudgy core demographic), I can see the appeal. For example, your Pudgy Penguin PFP can act as a protective avatar as you engage and explore online – allowing you to share only the personal information that you want to, while you build up trust with other community participants, and before you choose to meet IRL.

There was also a discussion about the difference between meme coins and NFTs – the short answer is that the former represent pure speculation, while the latter aim to create value for their holders. In fact, someone suggested that meme coin trading is not that different to punting on betting apps. But since most NFT collections are well down on their market highs of a couple of years ago, maybe NFT holders and communities like Pudgy Penguins are trying to convince themselves that they are still backing a winner?

Overall, however, I remain positive to the opportunities that NFTs represent – especially in the creative fields, and as a new model for IP licensing. Even if cute flightless birds from the southern hemisphere are not your thing, I don’t think you can dismiss or ignore the social, cultural and economic impact that NFTs will have.

Next week: “When I’m Sixty-Four”

 

 

AI & Music

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In a recent episode of a TV detective show, an AI tech dude tries to outsmart an old school musicologist by re-creating the missing part of a vintage blues recording. The professor is asked to identify which is the “real” track, compared to the AI versions. The blues expert guesses correctly within a few beats – much to the frustration of the coder.

“How did you figure it out so quickly?”

“Easy – it’s not just what the AI added, but more importantly what it left out.”

The failure of AI to fully replicate the original song (by omitting a recording error that the AI has “corrected”) is another example showing how AI lacks the human touch, does not yet have intuition, and struggles to exercise informed judgement. Choices may often be a matter of taste, but innate human creativity cannot yet be replicated.

Soon, though, AI tools will displace a lot of work currently done by composers, lyricists, musicians, producers, arrangers and recording engineers. Already, digital audio workstation (DAW) software easily enables anyone with a computer or mobile device to create, record, sample and mix their own music, without needing to read a note of music and without having to strum a chord. Not only that, the software can emulate the acoustic properties of site-specific locations, and correct out-of-tune and out-of-time recordings. So anyone can pretend they are recording at Abbey Road.

I recently blogged about how AI is presenting fresh challenges (as well as opportunities) for the music industry. Expect to see “new” recordings released by (or attributed to) dead pop stars, especially if their back catalogue is out of copyright. This is about more than exhuming preexisting recordings, and enhancing them with today’s technology; this is deriving new content from a set of algorithms, trained on vast back catalogues, directed by specific prompts (“bass line in the style of Jon Entwistle”), and maybe given some core principles of musical composition.

And it’s the AI training that has prompted the major record companies to sue two AI software companies, a state of affairs which industry commentator, Rob Abelow says was inevitable, because:

“It’s been clear that Suno & Udio have trained on copyrighted material with no plan to license or compensate”.

But on the other hand, streaming and automated music are not new. Sound designer and artist Tero Parviainen recently quoted Curtis Roads’ “The Computer Music Tutorial” (2023):

“A new industry has emerged around artificial intelligence (AI) services for creating generic popular music, including Flow Machines, IBM Watson Beat, Google Magenta’s NSynth Super, OpenAI’s Jukebox, Jukedeck, Melodrive, Spotify’s Creator Technology Research Lab, and Amper Music. This is the latest incarnation of a trend that started in the 1920s called Muzak, to provide licensed background music in elevators, business and dental offices, hotels, shopping malls, supermarkets, and restaurants”

And even before the arrival of Muzak in the 1920s, the world’s first streaming service was launched in the late 1890s, using the world’s first synthesizer – the Teleharmonium. (Thanks to Mark Brend’s “The Sound of Tomorrow”, I learned that Mark Twain was the first subscriber.)

For music purists and snobs (among whom I would probably count myself), all this talk about the impact of AI on music raises questions of aesthetics as well as ethics. But I’m reminded of some comments made by Pink Floyd about 50 years ago, when asked about their use of synthesizers, during the making of “Live at Pompeii”. In short, they argue that such machines still need human input, and as long as the musicians are controlling the equipment (and not the other way around), then what’s the problem? It’s not like they are cheating, disguising what they are doing, or compensating for a lack of ability – and the technology doesn’t make them better musicians, it just allows them to do different things:

“It’s like saying, ‘Give a man a Les Paul guitar, and he becomes Eric Clapton… It’s not true.'”

(Well, not yet, but I’m sure AI is working on it…)

Next week: Some final thoughts on AI