It may be hard to recall a time before iPhones (and their Android competitors) became the ubiquitous personal computing device. It’s now routine to pull a sleek slab of glass and aluminum from one’s pocket to look up flight prices or the name of a forgotten band or find some mindless entertainment to pass the time waiting in a queue or riding the subway to work. However, the iPhone was largely responsible for making the smartphone an indispensable accessory after similar devices failed to become a cultural phenomenon outside niche groups, like the BlackBerry with professionals.
AI seems to be having a similar moment with the rise of tools like ChatGPT, a tool that’s broken into the mainstream press, passed mock medical exams, and is just as likely to be a topic at a Fortune 500 Board of Directors meeting as the latest quarterly financial results.
Simplifying the Complex
The iPhone was a smash hit because it successfully combined complex technical features, a simplified user interface, and stylish packaging. On a feature-by-feature basis, there wasn’t much new on the iPhone versus competing devices from Microsoft and BlackBerry. Apple even decided not to allow 3rd party applications on initial versions of the iPhone, a feature that Microsoft and BlackBerry had provided for years, albeit through a rather clunky discovery and installation process.
Apple realized that “PC-like” functionality and interfaces were not appropriate for a device that fits in your pocket. While Microsoft tried to build tiny versions of its Windows operating system and Office applications, the original iPhone provided an intuitive interface focused on internet browsing, music, and personal communication.
The most important legacy of the iPhone was that it shifted consumer computing from a desktop- and laptop-centric experience to a mobile-focused experience for general users. While it might seem foreign to tech workers, the average individual may not even own a laptop or desktop computer, performing all their computing tasks through their smartphone or tablet.
Smartphones also opened the door to other computing devices, many based on similar hardware and relying on increasingly ubiquitous technology. Voice assistants like Amazon’s Alexa and Google’s Nest interact through speech.
ChatGPT may well be AI’s equivalent to the iPhone. Like the iPhone, it’s noteworthy not only because of its features or technical capabilities but its simple interface. Many of us recall an older relative or even a toddler picking up an early iPhone and immediately understanding how to interact with its interface. Sit similar individuals down with a ChatGPT window, and you’ll observe the same phenomenon: people naturally and immediately grasp how to interact with a complex and previously inaccessible technology.
With the iPhone, this accessibility allowed millions of individuals access to connected computing. It inspired an entire economy of app developers and accessory makers to meet the needs of those individuals. iPhones became everything from music players to video cameras to sources of juvenile amusement, ranging from the infamous “Fart app” to complex multi-user games.
From Accessibility to Productivity
When the iPhone made mobile, always-connected computing available to the mass market, it triggered an explosion of not only new apps and accessories but entirely new business models. Businesses like Uber required cheap mobile computing, just as social media exploded with the rise of constant access and a high-quality camera in your pocket.
In AI, this explosion of accessibility is just beginning, and millions of individuals that have never knowingly used a complex AI engine can now interact with ChatGPT. The more nefarious-minded or generally lazy are using the tool to cheat on school assignments, triggering the development of tools to detect or digitally “watermark” AI-generated text, just as people are being exposed to AI-related ethical questions previously limited to academics and researchers.
However, just as fart apps and other seemingly-trivial technologies created familiarity and interest in the app store, so too will using AI to finish your homework and identify new applications and business models for the new technology.
Applying AI to Your Teams
While it might seem like a distant memory, the arrival of the iPhone also disrupted most workplaces. Many companies faced a seemingly-existential crisis on whether to allow iPhones to interact with “enterprise” technologies, especially since they lacked the robust corporate controls of the competing BlackBerry devices. Some companies embraced “Bring Your Own Device” policies and allowed individuals to use company email and collaboration apps on their chosen devices. In contrast, others fought a losing battle to keep the devices off their networks.
Similarly, many companies are trying to decide whether to “allow” AI tools in the workplace. There are certainly legitimate concerns, particularly around data sharing. Each interaction with tools like ChatGPT informs and modifies the underlying algorithms, as much of their strength comes from this ability to “learn” from past interactions. Sharing confidential data, from personal information to company secrets or medical records, ultimately releases that data “into the wild.”
Others worry about the ethics of allowing employees to use AI-based tools to perform their jobs. While this might seem like an incredibly modern concern, this line of thinking has appeared with every new technology. With the dawn of the PC, supervisors likely worried about whether to allow typists to use newfangled word processing software, just as managers worry that an AI might generate a subordinate’s PowerPoint slides.
This use of technology isn’t “cheating” any more than a Google search is cheating versus going to the local library. However, it will require a shift in training and managing our workforce. People that were “individual contributors” and usually the ones performing tasks like research, content creation, etc., can now be equipped with an infinitely expandable team of AI collaborators. Rather than spending days assembling slides, this individual might use one AI to create an outline, another AI to generate a key chart, and yet another AI to edit and optimize the text before performing a final review.
Rather than attempting to “ban” these technologies, inform your teams of the risks of data leakage, and encourage them to experiment. If you can imagine what might happen if a team of competent analysts supported each of your individual contributors, you can conceptualize the benefits and changes that might be required in the reasonably near future.
Apple’s iPhone moment cemented the smartphone’s status as the dominant platform for computing, pushing aside the traditional personal computer for most of the world’s population. It changed how we consume technology, how we work and ultimately allowed for new business models and innovations. ChatGPT may well be a similar moment for artificial intelligence, and it’s worth understanding its impact and allowing your teams to adopt and experiment to avoid being left behind.
If you enjoyed this, be sure to check out our other AI articles.
