AI in healthcare is a really broad topic.
We have hundreds of great examples on how we can put it to use and create applications
that help with CT scan analysis, make robots that assist with surgery or accelerate MRI
imaging.
Can AI replace a professional doctor?
No, and we already discussed that a couple of weeks ago…
You can click on the link below to see what it was all about.
But it can definitely, be your best friend in this unequal fight between life and death.
Especially in the face of the latest threat known to humanity as – COVID19.
Or can it?
Good Morning When covid-19 struck Europe in March 2020,
the medical sector plunged into a health crisis that was still quite badly understood.
The AI community, in particular, rushed immediately to develop software that many believed would
allow hospitals to diagnose patients faster, bringing much-needed support to the front
lines—in theory.
According to the latest article published by MIT Technology Review, hundreds of AI tools
have been built to catch covid, none of them made a real difference, and some
were even potentially harmful.
That conclusion is not anyone’s subjective opinion, but a result of multiple studies
published over the last few months.
In June, the Turing Institute, the UK’s national center for data science and AI, put
out a report summing up discussions at a series of workshops it held in late 2020.
The clear outcome was that AI tools had made little, if any impact in the fight against
covid.
The report says clearly, that AI technology will never be able to handle diagnostic tasks
anymore and humanity should stop developing those algorithms.
No it doesn’t, but many people would probably think that way, since we finally had a great
occasion to test out AI’s capabilities on a real battlefield and it failed.
But the problem appears to be more human-related, mostly linked to the poor quality of the data
that researchers used to develop their tools.
Information about covid patients, including medical scans, was collected and shared in
the middle of a global pandemic, often by the doctors struggling to treat those patients.
Researchers wanted to help quickly, and these were the only public data sets available.
But this meant that many tools were built using mislabeled data or data from unknown
sources.
That means you should always make sure of your dataset quality and label your data properly.
For example using Snorkel AI platform.
Which has announced on August 9th that it has raised $85 million in a series C round,
giving them the total score of $135 million raised and a value of $1 Billion dollars.
Founded in 2019 by a team spun out of the Stanford AI Lab and engineers hailing from
Apple, Facebook, Google, Microsoft, and Nvidia, Snorkel enables companies to build AI-powered
apps with “programmatic” data labeling, with the goal of minimizing the need to hand-label
model training data.
Everyone knows that proper data labeling is one of the biggest struggles for AI development
and the more we invest into it’s development, the better for everyone.
AI code creation subject has also been struggling with Intellectual Property matters.
Examples like, GPT-3 creations or OpenAI Codex used for GitHub’s Copilot are being constantly
questioned whether they should be considered under AI laws.
A german researcher and a former MEP Julia Reda, points out that: “Copyright law has
only ever applied to intellectual creations, which means that if there is no creator - there
is no work,” Usually, that would mean machine-generated
code like that of GitHub Copilot is not a work under a copyright law, since it cannot
be considered as creator.
But that’s Europe … and Australia decided to think differently.
A federal court in Australia has ruled that AI systems can be credited as inventors under
patent law in a case that could set a global precedent.Ryan Abbott, a professor at University
of Surrey, has launched over a dozen patent applications around the world – including
in the UK, US, New Zealand, and Australia – on behalf of US-based Dr Stephen Thaler.And
here comes the plot twist: it’s not Thaler which Abbott is attempting to credit as an
inventor, but his AI device known as DABUS that consists of neural networks and which
was used to invent an emergency warning light, a food container that improves grip and heat
transfer.
DABUS was awarded its first patent for “a food container based on fractal geometry,”
by South Africa’s Companies and Intellectual Property Commission on June 24.
Whether AIs should be granted certain “rights” similar to humans is a key debate, and one
that is increasingly in need of answers.
This patent case could be the first step towards establishing when machines – with increasing
forms of sentience – should be treated like humans.And whether they will or not depends
on us – their creators.
And it would be better if “treated like humans” could mean “treated with dignity,
compassion and respect”.
After all…
AIs should also create things to keep changing the world…. for better.