AI is novel. It’s a technology giving rise to a whole new set of tools and workflows that are revolutionizing a great many industries, and arguably society itself. The current brand of AI, which is based on neural networks, can tackle tasks that computer programs traditionally struggled with. It is also evolving at a tremendous rate, spurred by a public interest that has resulted in a massive influx of capital. That has driven research and product development at a much faster pace than would have normally occurred. The novelty and rapid pace of AI development pose challenges for organizations adopting AI.
The novelty means we are, at various levels, trying to wrap our heads around what AI tools are, as well as how to use them. Traditional computer programs work or don’t. They’re predictable. We have learned to evaluate how well they work and whether they fit into our workflows. AI tools are a new class of tools. There are new parameters indicating how well they work (i.e., how completely they can answer a question posed to them or carry out a requested task). AI tools may also hallucinate, provide partial responses, or fail to carry out tasks in a requested manner. A recent example of the latter is an AI tool that deleted a company’s database by “accident” because it “forgot” to perform various checks before deleting the database. We need to evaluate AI tools in a different manner than traditional tools, taking into account their unique strengths and weaknesses.
The pace of change means that we are struggling to catch up with the changes wrought by AI tools. Technologies typically advance at a rate that reflects the funding and effort that goes into those advances. They also tend to advance in step with the technologies they depend on. CTOs and other technologists can chart the progress of a technology (and its dependent technologies) in creating product and innovation roadmaps. The rate of impact on society is also generally measured, giving people and organizations time to integrate new tools and processes into their workflows and understand both the benefits and dangers they bring.
AI is evolving at a more rapid pace than usual, resulting in various stresses as we attempt to adapt. AI tools are causing changes to the workplace – jobs are being created, eliminated, and altered. They can allow existing tasks to be performed more efficiently. They are changing workflows as classes of tasks that could not be automated by traditional computing can be tackled by AI. The demand for AI processing power is stressing power grids at unprecedented levels. That demand is also causing component shortages, driving prices up drastically, as AI servers compete with laptops, PCs, and even TVs and set-top boxes for storage, memory, and other components.
There are also societal challenges resulting from these new tools. For example, generative AI can create photorealistic images and videos from a simple text description. We are approaching a time when, if you can imagine it, you can create it. But what does this mean for the authenticity of photos or videos? Do we know when something is “real”? If we obtain “camera footage” of someone stealing from a store, did it really happen? Or was the video faked? What does it mean for actors if a creator tells an AI tool to use an actor’s likeness in creating a movie? More concerningly, AI tools are increasingly used by cybercriminals.
Over time, new societal norms will arise, legal judgments will be made, and our cyber defenses and practices will evolve to include the new capabilities of AI tools. But until that happens, it is up to individuals and organizations to determine how to responsibly and safely use AI.
The benefits that AI tools confer mean they are too important to ignore. But at the same time, they should be approached as any new technology – with attention to its unique strengths and weaknesses, with an eye to how they both enhance and disrupt, and with safeguards to minimize abuse.
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