In AI, we trust?

Quite a busy week it has been. Let's start with a more quirky story.

Do you know what this is?

That's a fluffy purple bunny. Well, at least according to DALL·E, a neural network that creates images from text captions.

I think it's safe to say that I won't be abandoning my day job anytime soon.

Access is open to all and you can try it here .

But why create an image if you can create a synthetic video? (Don't answer that. It's a rhetorical question.)

Using a text description or an existing image, Make-A-Video (by Meta) can now render video on demand. Similarly, Google just announced the development of Imagen Video, a text-to-video AI mode capable of producing 1280×768 videos at 24 frames per second from a written prompt. Now imagine the fake purple bunny in a video.

But that brings me to the question of the week: If we can no longer trust what we see, when our brains become trained to question the authenticity of everything (or even everyone) that we see digitally, what does that mean to society, where trust is the foundation of any functioning democracy and is essential for tech adoption?

Trust is what binds us.

The very topic of trust is addressed in a new report by Economist Impact , sponsored by 赛仕软件 , which explores major forces that stand to reshape the future of banking by 2035, and presents three potential scenarios as well as challenges and opportunities facing banks between now and 2035:

• Can transformed banks regain public trust?
• Might banks catalyze cross-industry climate action and power the green transition?
• How will banks fare in a geopolitically fragmented world?

I will be exploring the findings from the study with the brilliant Alex Kwiatkowski at the upcoming Sibos in Amsterdam. Join us for the session "Embedding Generosity Into the Global Economy" on Wednesday, Oct. 12, at 12:30 p.m. CEST, at the Meet the Experts stage.

While we are on the topic of trust and ethics, the White House just published an AI Bill of Rights that instructs banks and other companies on the kinds of consumer protections they need to build into their AI-based programs.

It's a good step in the right direction. Or rather, it has good intentions. At the very least, this sends a signal to the industry: "Hey, we are watching."

That said, however, I can't help but feel that we are a bit late to the party, especially when even the Vatican has weighed in on the subject, not to mention the EU. More concerning is that this is nonbinding with no enforcement measures, like a toothless tiger. It will be up to lawmakers to propose new bills. And even when anything is passed, having laws is one thing, reinforcing them is another.

When we look across the ocean, GDPR, for instance, went into effect 4 years ago, and companies who don’t comply get hefty fines. Since then, the EU has also proposed legislation that govern the use of AI in special high risk areas, including loan applications. The million dollar question is, will we be able to follow suit? And if so, when? Or will we be subjected to the whims of the political winds? (I fear it will be the latter.)

You can read Penny Crosman 's excellent write up here .

Another interesting point to note in the White House document:

• You should know how and why an outcome impacting you was determined by an automated system, including when the automated system is not the sole input determining the outcome.
• You should be able to opt out, where appropriate, and have access to a person who can quickly consider and remedy problems you encounter.

How this can be implemented/supported is an intriguing question. This is not as simple as opting out from telemarketing. And asking a bank to provide access to someone who can quickly consider and remedy something this complicated is easier said than done.

Much has been discussed around the need to prevent discrimination by algorithms. While it might not be the intention of the algorithm to discriminate, in reality, they likely do, due to the data that is being used is based on historical discrimination. It’s the classic "garbage in, garbage out".

The story from Markup.org provides an excellent example: "An investigation by The Markup has found that lenders in 2019 were more likely to deny home loans to people of color than to White people with similar financial characteristics—even when they controlled for newly available financial factors that the mortgage industry for years has said would explain racial disparities in lending." This is a topic that I have explored with Mia Shah-Dand at the recent Finovate New York as well. You can watch our panel here .

Be a good human.

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In this week's One Vision episode ...

In recent years, artificial intelligence has become an integral part of our daily lives, driving much of what we do and what we experience. Financial services is no exception. To meet the needs of changing demographics, being able to attract and retain the right talent is crucial.

In this episode of One Vision, I chat with Abhijit Bose , MVP, Head of Center for Machine Learning and Enterprise ML Platforms at Capital One , on financial services innovation and how the bank is leveraging AI and machine learning to improve customer experiences. As the line between banking and technology continues to blur, the time is now for banks to nurture talent of today to tackle the challenging questions of tomorrow.

Give this episode a listen and let us know what you think.

"The future is now: Banking in a changing world."

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Beyond Good is available now on Amazon, Barnes & Noble,?Bookshop.org , Kogan Page and anywhere books are sold. You can check out what others are saying about our book?here .

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