Understanding what your AI models are doing is super important both from a functional as well as ethical aspects. In this episode we will discuss what it means to develop AI in a transparent way.

Mehrnoosh introduces an awesome interpretability toolkit which enables you to use different state-of-the-art interpretability methods to explain your models decisions.

By using this toolkit during the training phase of the AI development cycle, you can use the interpretability output of a model to verify hypotheses and build trust with stakeholders.

You can also use the insights for debugging, validating model behavior, and to check for bias. The toolkit can even be used at inference time to explain the predictions of a deployed model to the end users.

Learn more:

Deepfakes have started to appear everywhere.

From viral celebrity face-swaps to impersonations of political leaders – it can be hard to spot the difference between real and fake.

Digital impressions are starting to have real financial repercussions. In the U.S., an audio deepfake of a CEO reportedly scammed one company out of $10 million.

With the 2020 election not far off, there is huge potential for weaponizing deepfakes on social media.

Now, tech giants like Google, Twitter, Facebook and Microsoft are fighting back. With Facebook spending more than $10 million to fight deepfakes, what’s at stake for businesses, and what’s being done to detect and regulate them.

Lex Fridman interviews Keoki Jackson, he CTO of Lockheed Martin.

Lockheed Martin is a company that through its long history has created some of the most incredible engineering marvels that human beings have ever built, including planes that fly fast and undetected, defense systems that intersect threats that could take the lives of millions in the case of nuclear weapons, and spacecraft systems that venture out into space, the moon, Mars, and beyond with and without humans on-board.

Law enforcement agencies like the New Orleans Police Department are adopting AI based systems to analyze surveillance footage. WSJ’s Jason Bellini gets a demonstration of the tracking technology and hears why some think it’s a game changer, while for others it’s raising concerns around privacy and potential bias.

As the machines are get smarter, they have reached the point where they learn by themselves and, even make their own decisions.

Here’s an interesting look at 10 times AI displayed amazing capabilities

There are machines that dream, read words in people’s brains, and evolve themselves into art masters. The darker skills are enough to make anyone […]

Here’s an interesting article in Nature about the use of AI in evaluating embryos with AI — another use of computer vision in the medical field. Could this bring down healthcare costs? What if the algorithm mislabels an embryo? Are there ethical implications?

Deep learning algorithms, in particular convolutional neural networks (CNNs), have recently been used to address a number of medical-imaging problems, such as detection of diabetic retinopathy,18 skin lesions,19 and diagnosing disease.20 They have become the technique of choice in computer vision and they are the most successful type of models for image analysis. Unlike regular neural networks, CNNs contain neurons arranged in three dimensions (i.e., width, height, depth). Recently, deep architectures of CNNs such as Inception21 and ResNet22 have dramatically increased the progress rate of deep learning methods in image classification.23 In this paper, we sought to use deep learning to accurately predict the quality of human blastocysts and help select the best single embryo for transfer (Fig. 1).

Here’s an interesting piece in Forbes on how AI will transform the way we conduct and audit business.

“One of the best-use cases for AI is to look at information and to identify patterns that stand out,” he says, adding that this applies just as readily to looking for unethical behavior as it does to recognizing cat pictures. “As long as there’s data related to it and you can analyze it at scale, AI can detect anomalies that humans simply can’t.”