For conversational AI, there are many contenders for winner, and probably there will be a winner who rules all, because they are all being trained on public data (the Internet).

For using AI to create images in Photoshop, or spreadsheets in Office, they already have monopolies, and those abilities will simply cement the monopolies further.

But there is a world of potential uses that need to be trained on private data, and that will help one AI business rise to the top. First mover advantage from training on private data.

Example:

In business meetings with client I often need to recall data to respond to a question. It is far better for me to know it off the top of my head, than “excuse me while I look for it”. AI can listen the conversation, and based on its learning, know which data to surface for me, and present it on my screen or AI spectacles.

That takes training. A company like Zoom could (with permission) listen in on meetings and get a head start.

Don’t be surprised if Microsoft wins. They already have Office and Teams. They already have OpenAI. And they can easily buy the companies who can access the private data for training.

Google doesn’t have the same potential for data access. Far fewer people use their platforms for meetings.

The other angle is hardware. If Apple can get their AR glasses out there en masse in businesses, those glasses can listen in (with permission) and learn.

Amazon won’t even partake, thankfully. But they will go after home automation (a talking house), but never be sufficiently innovative to own that space, and hopefully do not buy the winner.

This is good news – a series of guidelines aimed at protecting the American public from burgeoning technologies that utilize artificial intelligence (AI). Here’s my take on how the 5 principles could affect one of the biggest services of all, Google Ads.

“Safe and Effective Systems” – Google have hubris and will resist any external input into how safe theirs is.

“Algorithmic Discrimination Protections” – only covers what is already enshrined in law as discrimination, like race and gender. Google has always been keen to not fail on this one.

“Data Privacy” – again, won’t be an issue, in the US. Google does have problems with using a global network of servers storing the data from particular countries who do not like that practice.

“Notice and Explanation,” argues that users should know whether an automated system is being used by a company in the first place by providing “generally accessible plain language documentation” that includes “clear descriptions” of how the system functions.

This is a big problem for Google. While they can cite commercial sensitivity for many things, they will struggle to simply explain how the machine learning does what it does. Already support staff cannot explain decisions that affect the account. However, the language of the guidelines also mention calibrated to the level of risk based on the context, and Google could argue that there is no risk, therefore nothing needs explaining. And they would have a point. Results can be judged daily, and the service discontinued if not satisfactory.

“Human Alternatives, Consideration, and Fallback” – this is the biggie.

“You should have access to timely human consideration and remedy by a fallback and escalation process if an automated system fails, it produces an error, or you would like to appeal or contest its impacts on you,” the blueprint says. “Human consideration and fallback should be accessible, equitable, effective, maintained, accompanied by appropriate operator training, and should not impose an unreasonable burden on the public.”

Google Ads suspends advertisers based on risk profiles created by machine learning. Such suspensions, from the dominant search advertising platform, can destroy livelihoods.

Google suspends accounts that look and feel like bad advertisers, without proof, and without much in the way of genuine recourse.

Google Ads is trending towards doing without humans altogether, and this is exactly the type of law we need to stop such things from happening. We cannot have a world where “the computer decided” is the final word.

I have often wondered about how Artificial Intelligence can be its own person, with money and control, a very scary proposition.

The problem is that ownership can only be assigned to people. Yes, a business or trust can own something, but neither can exist without people controlling them.

But now… Australia has decided that AI can own a patent. That means that AI can get an income, on its own. I can see future court cases arguing that if an AI can receive an income, it must be able to open a bank account, own property and so on.

Robot overlords are not far away.

(Note, a US court said no to an AI system owning a patent)

UPDATE: Ruling overturned in Australia, so currently nowhere lets this happen. In South Africa AI has been provisionally approved… but that just means they haven’t really looked at it yet.