Artificial Intelligence is spending a lot of time in the headlines lately. Just this past week, news circulated about an AI project called “ChatGPT” that successfully passed the MBA exam from a prestigious law school. AI has also recently been making news as graphics, art, and images are being artificially generated, causing quite a disturbance among the art and creative communities. And let us not forget about the “deepfake” technology enabling people to artificially be inserted into video and audio recordings.
So why did AI seem to suddenly appear overnight? The truth is, it didn’t.
Developers and scientists have been working on AI principles and technologies for decades. In fact, the earliest theoretical works in AI can be traced back to 1935 to Alan Turing (yep. The Turing test guy). He gave a speech in London in 1947 where he discussed computer intelligence, saying “What we want is a machine that can learn from experience” and that the “possibility of letting the machine alter its own instructions provides the mechanism for this”. Turing also predicted that computers would be able to play chess at a high level, and in 1997 a computer named “Deep Blue” that was built by IBM beat Garry Kasparov, the reigning world chess champion in a six-game match. At that time, Deep Blue used 256 processors working together, enabling the computer to evaluate 200 million chess positions per second.
Today, AI is being deployed across all disciplines of technology. Be it medicine, health, computer technologies, writing, video and audio, programming, the list goes on and on. Researchers have used an artificial-intelligence network called “AlphaFold” to predict the structures of more than 200 million proteins for 1 million species, covering almost every known protein on the planet. Another recent example of AI engagement is the “Github Copilot”. Github is used by developers to store and manage their code, as well as to track and control changes made to their code. Copilot AI turns natural language prompts into coding suggestions to expedite programming. Imagine just putting in words to explain what you want to do and the Copilot just giving you the code.
AI is growing at an exponential rate, and appearing across virtually every known scientific, medical and technology discipline. But are there downsides?
Technology itself isn’t either inherently good or bad. Technology is a tool that we as humans develop, and continue to evolve to help us achieve. So, it can be used for virtually any application, system or methodology we point it at. The potential downside comes when we factor in the human element. To be more specific, the evolution of technology and AI downsides reside in “who is controlling it?”.
There are two sides to consider when contemplating the long-term vision for Artificial Intelligence. You have the “User” and you have the “Provider”. Each of these people have a motivation for their engagement with AI technology.
As an example, Let’s look at Alexa. From a user perspective, Alexa is a very powerful in-home AI driven device that can easily manage a smart home. A user of Alexa may wish to buy the device to power their music and lighting. Maybe they just got their first place and they’re trying to make it a very interactive and engaging place to enjoy the company of friends or romantic interests. Alexa can easily find the right song for the moment, and can even set the lighting to something more mood appropriate. Perhaps even turning on a disco ball. . .but I digress.
The point for the user is that there are a variety of motivations that may be poking and prodding the user to bring the device into their home. But what about the motivation of the provider? What’s driving Amazon to develop and provide Alexa devices?
Clearly, I can only speculate on what the true motivations are, but a quick online search (yes, I just used AI to pull up an article I’m looking for) shows that there was a lawsuit against Amazon that alleged the Alexa device is “spying on you”. More specifically, the complaint filed on behalf of a number of plaintiffs said the case came out of “Amazon’s practice of using smart-speaker technology (“Alexa”) to save permanent recordings of millions of Americans’ voices without their knowledge or consent. The complaint further stated that “Amazon then indefinitely and permanently stores a copy of that recording on its own servers for later use and commercial benefit, warehousing billions of private conversations in the process”.
Still, other quickly searchable data reveals that “Whatever information you ask Alexa is not only collected by Amazon and third-party tracking services but also shared with as many as 40 advertising partners.” So, what is Amazon’s motivation for developing and selling the Alexa device? Again, I cannot speak for anyone but myself, but I would guess that Amazon isn’t just “sharing” information with advertising partners from the kindness in their hearts. So perhaps, the motivation may be as simple as opening 40 new revenue streams for selling a single product.
Another example can be made with video games. Like many of you reading this article, I enjoy taking time to play a game. Let’s face it, games are fun, engaging, and give our minds an opportunity to just simply get lost for a while and regenerate while we are being entertained. Games for smartphones, computers, and consoles are popping up virtually daily and offer “free to play” engagements. But how are they free?
The motivations behind most free-to-play games are to get you engaged so that you’ll spend as much time as they can get you to spend in front of your screen and to convince you to spend your money on items to “enhance” your gaming experience. The secret here is that there isn’t a secret. These gaming companies are out to make money. My money and your money. And to do this, they need you playing their game. So, they create free models to get you engaged, then dangle shiny prizes at you that are seemingly at very affordable prices, so we jump in. The provider of the technology has a vested interest in getting you engaged in their game so that you’ll be willing to spend your money on their product.
That all makes sense, but what does that have to do with AI? Are these games using AI?
Yes…they are using AI. Each time we engage our devices, we leave a trail. The devices (via the operating software) know how long we’ve been on our device, how often we engage our device, how much time we spend each time we engage our device, and generally every action we take while engaging our device. This information is parsed (through AI) to establish patterns. These patterns are used to market and sell products and services to you, based on the actions you routinely take while engaging your device. This isn’t a revelation or some new concept that I’m sharing with you now. We all know these things are happening, but we continue to engage.
To summarize the User and Provider aspect of AI engagement, we need to remember that AI isn’t really anonymous. There is a provider that enables the AI we engage, and ourselves, the users who engage it. The motivations of these parties shape the experience(s) that AI provides.
So what about privacy? Is AI impacting my privacy?
In short, yes. It is directly impacting your privacy. As I shared above, AI in gaming as an example is collecting a significant amount of data on your engagement with that game so that the game can introduce things to you that cost money. The things you’ll see are going to be specifically focused at how you engage the game. This is the same thing that happens when you watch any streaming services or engage anything in online shopping. How many times have you got to purchase something online and been inundated with advertisements for the very products and/or services you were just shopping for? Or when you watch a streaming service and all the recommended videos appear to have similar aspects to the video you just watched.
Yep. Its AI. And yes, it is watching you intently to ensure it matches you with products and services you’re already showing interest in so that you’ll spend your money.
Ok, then what’s next?
This is an interesting question because the real answer is nobody knows. However, if we look backward in our timeline we can see the introduction of a plethora of fascinating and engaging technologies that brought both hope and fear, yet we as humans continue to evolve and adapt these revolutionary technologies into our lives.
I’m guessing there is a group of people reading this article who remember record albums. In my town, they came out on Tuesdays and you needed to be at the record store if you wanted to see what was new in music. There’s also another group of people that only remember CDs and DVDs. Still another group that may only recall using digital media such as MP3s. Some of you remember a time before smartphones and the internet. Others of you don’t.
The point of all of this is that regardless of the technologies that emerge, we’ve always taken the best aspects of them and woven them into our lives. Think about a 15-year-old that knows more about how to fix a computer than you or I do. It’s because that’s part of the world that a child has grown up in. It’s a part of the world that is familiar and well-known. So from an early age, the child has adapted to engage that technology.
No matter where technology and AI take us, I believe we will adapt. We will learn to engage these emerging technologies and weave them into our daily lives. People have occupied this planet for thousands of years. We cannot underestimate our own ability to adapt and evolve. After all, I could have even used AI technology to write this article. . . . . . .but did I?
Sources:
NBC News | ChatGPT Passes MBA
https://www.nbcnews.com/tech/tech-news/chatgpt-passes-mba-exam-wharton-professor-rcna67036
The Guardian | It’s the Opposite of Art
https://www.theguardian.com/artanddesign/2023/jan/23/its-the-opposite-of-art-why-illustrators-are-furious-about-ai
Wikepedia | Deepfake
https://en.wikipedia.org/wiki/Deepfake
Encyclopedia Britannica | Alan Turing and the beginning of AI
https://www.britannica.com/technology/artificial-intelligence/Alan-Turing-and-the-beginning-of-AI
Encyclopedia Britannica | Deep Blue
https://www.britannica.com/topic/Deep-Blue
Nature | The entire protein universe: AI Predicts the shape of nearly every known protein.
https://www.nature.com/articles/d41586-022-02083-2
GitHub | Copilot AI
https://github.com/features/copilot
Komano.com | Report says Alexa voice data used to send you targeted ads
https://www.komando.com/security-privacy/alexa-targeted-ads/836536/
The Street | Lawsuit Alleging Amazon’s Alexa is Spying on You Moves Forward
https://www.thestreet.com/technology/amazon-loses-a-round-in-alexa-privacy-lawsuit
