No ratings yet.

Recently the Cyber Defence Agency of the United States posted an alert regarding the threat of synthetic media, such as deepfakes. They warned us for the exponential increase in deepfake videos and the technology that comes with it (NSA, FBI, and CISA release Cybersecurity Information Sheet on Deepfake threats | CISA, 2023). Also, the BBC had an article related to the dangers of deepfake. They discussed the scam videos that were made via deepfake about famous youtuber MrBeast. These videos were targeting fans showing them how they could win an iPhone by providing private information (Gerken, 2023).

Reading this made me interested in deepfake and I wanted to find out how difficult it is to make such videos using this technology.

Deepfake

However, it is first important to understand what deepfake is. According to MIT, the term deepfake refers to synthetic media where the person in a video or an image is replaced with another person’s likeness (Deepfakes, explained | MIT Sloan, 2020).

Basically, Deepfake technology refers to an artificial intelligence method that modifies or creates videos, audio, and images of individuals. Fundamentally, it employs machine learning algorithms to scrutinize, replicate, and mimic a person’s voice or facial expressions found in source media like videos or images (Clark, 2023). Recently for example, Mark Zuckerberg could be seen in a video talking about how great it is to have information about millions of people:

‘Imagine this…’ (2019) This deepfake moving image work is from the ‘Big Dada’ series, part of the ‘Spectre’ project. Where big data, AI… | Instagram

Own experience

So, I tried to use D-ID a website where you can make videos using free deepfake technology. If you pay for the premium version, you can make longer videos and use better technology. However, for this test and to look for easy solutions I wanted to use the free version and see how accurate this is.

First, I typed in my own name on Google to see which pictures I could find of myself on the web. It showed me an old twitter (X) photo and my current LinkedIn profile picture:

To blend in as a ‘scammer’, I made a screenshot of my own LinkedIn profile and used this as input for D-ID. This is the result:

It scares me how I look and also should you, but the most frightening is, is that everyone could basically do this with the free information that Google provides. Moreover, if this is already for ‘free’, how would advanced deepfake look with my own picture?

Luckily the technology is not ‘that advanced yet’. Seeing the examples of myself, Mark Zuckerberg, and MrBeast multiple times it is actually quite easy for me to conclude that this is, of course, not real. However, for some target groups (e.g., minors) this could look realistic which brings up the ethical part of this technology.

Also, the Cyber Defence Agency of the United States is already preparing to warn and help organisations in advance for this kind of technology. They collaborated with the National Security Agency (NSA), the Federal Bureau of Investigation (FBI), and the Cybersecurity and Infrastructure Security Agency (CISA) and came up with a document regarding the threats deepfake poses to organisations, you can read it here if you would like to:

https://www.cisa.gov/news-events/alerts/2023/09/12/nsa-fbi-and-cisa-release-cybersecurity-information-sheet-deepfake-threats

Of course, there will be examples of this technology helping the society we live in, however there are some serious downsides that we need to address as well.

Should this technology be free for everyone to use, like D-ID? How far can we go with this type of technology?

Sources used:

Gerken, B. T. (2023, 4 oktober). MrBeast and BBC stars used in deepfake scam videos. BBC News. https://www.bbc.com/news/technology-66993651

NSA, FBI, and CISA release Cybersecurity Information Sheet on Deepfake threats | CISA. (2023, 12 september). Cybersecurity and Infrastructure Security Agency CISA. https://www.cisa.gov/news-events/alerts/2023/09/12/nsa-fbi-and-cisa-release-cybersecurity-information-sheet-deepfake-threats

Deepfakes, explained | MIT Sloan. (2020, 21 juli). MIT Sloan. https://mitsloan.mit.edu/ideas-made-to-matter/deepfakes-explained

Clark, M. (2023). Understanding deepfake technology: how it works and concerns arising from its implementation. pctechmag.com. https://pctechmag.com/2023/05/understanding-deepfake-technology/

No ratings yet.

According to Insider, out of 73,257 NFT collections, 69,795 of them, or slightly over 95%, had a market cap of zero (Rosen, 2023). Therefore, I wanted to start a discussion and look into generative AI for creating images and their relation to NFTs (non-fungible tokens). Perhaps this could be the reason for the crash.

DALL-E & Bing

First, I wanted to investigate one of the AI tools that is used for creating images: DALL-E and Bing. DALL-E is developed by OpenAI, who is also famous for ChatGPT. DALL-E uses a variant of GPT-3 (powerful language processing AI) to understand the text inputs and generate corresponding images.

When you start up Microsoft Edge and you have applied to the Bing beta like I have, you can let Bing AI, that runs for its ‘art creation’ on DALL-E, create images for you based on your text input. For example, I created this image based on this prompt:

“Create an image with this prompt: A shark eating blockchains (NFT) and little US dollars and euros.”

If it is this easy to create digital art and ownership, could this be the reason for the overall decline for NFTs?

NFTs

For those who do not know, NFTs were first introduced to the online community in 2012. The first known NFT, called “Quantum”, was minted on May 3, 2014, by digital artists Kevin McCoy and Anil Dash (Creighton, 2022). To continue, NFTs are unique, non-replicable cryptographical tokens that are existing on a blockchain. These tokens are used to represent ownership of exclusive, rare, or unique content. An example is the NBA Topshot platform were users can sell their rare NBA moments. Unlike cryptocurrencies such as Bitcoin, which is fungible and can be exchanged on a one-for-one basis, NFTs have values of their own and cannot be exchanged in this way.

Hype

The hype surrounding NFTs reached its highpoint in 2021 with a $2.8 billion in trading volume recorded in August 2021 alone (Hategan, 2023). This drove NFTs into the global spotlight, with media reporting on multi-million-dollar transactions involving specific NFT assets.

The initial excitement surrounding this new form of digital asset led to what seemed like a gold rush according to Dappgambl (2023). However, as said earlier, the current state of the NFT market is an utter contrast to its early days. According the The Block, the weekly traded value in July 2023 was around $80 million, a mere 3% of its peak in August 2021. So, what could have caused such a shift?

Can generative AI be related to the crash in June?

I personally think that the upcoming of more advanced AI for images is one the reasons that NFTs are decreasing in value. What you saw in my previous example, it is extremely easy to create digital content and claim ownership. However, I do not want to be shortsighted. It is also important to consider other factors. The NFT market is influenced by a variety of elements, including overall interest in the art world, (especially) economic climate and demand in cryptocurrencies. Ethan McMahon, a Chainalysis economist, (sort of) confirmed this by saying:

“This decline is definitely linked to the broader slowdown in crypto markets,” (Milmo, 2022)

From my perspective, Generative AI has made it easier for anyone to create digital art, and therefore increasing the supply of digital art available for ‘tokenization.’ In simple economic terms: If supply grows faster than demand, this could lead to a decrease in average prices.

What do you think? How big is the exposure of generative AI to the enormous value decrease of NFTs?

Sources

Rosen, P. (2023, 21 september). Remember when NFTs sold for millions of dollars? 95% of the digital collectibles may now be worthless. Markets Insider. https://markets.businessinsider.com/news/currencies/nft-market-crypto-digital-assets-investors-messari-mainnet-currency-tokens-2023-9

Creighton, J. (2022, 15 december). NFT Timeline: The Beginnings and History of NFTs. nftnow.com. https://nftnow.com/guides/nft-timeline-the-beginnings-and-history-of-nfts/

Hategan, V. (2023, 29 augustus). 95% of NFTs are dead – Trends, Predictions & Statistics 2023. dappGambl.com. https://dappgambl.com/nfts/dead-nfts/

Milmo, D. (2022, 2 juli). NFT sales hit 12-month low after cryptocurrency crash. the Guardian. https://www.theguardian.com/technology/2022/jul/02/nft-sales-hit-12-month-low-after-cryptocurrency-crash

---