DALL·E 2 – OpenAI’s realistic image generation system, is a developed artificial intelligence that creates detailed images from text descriptions. On their website they illustrate how different subjects and descriptive words can be strung together to produce incredibly accurate and vivid results – equal to the power of a child’s imagination.
Text can be as simple as “a dog playing fetch”, to “a purple dog playing fetch in space, wearing a neon pink tutu, and being chased by a marble statue of George Washington.”
Merzmensch Kosmopol, [@Merzmensch]. (Apr 27, 2022). Twitter. URL
Portrait of the Future of Work
In Hollywood, AI takeovers are a profitable and entertaining fear and fascination. From 2013’s “Her”, to “The Matrix”, we’ve all wondered – how long before this is reality? Now, we’re surely not here as harbingers of a dark tech future for the world – or for the workforce (at least not yet), because ironically, it lacks the imagination.
If you’re a reader of our Tech Insights, you’ll know we talk a lot about automations and how automating processes helps to streamline workflows and increase productivity. Automations are a good way to begin processing the capabilities of AI. An automation is a process, a job that completes one task, and multiple steps are used to create an automation’s flow. Whether this is sending an alert based on the parameters in a dataset, or triggering an email when someone signs up for your service.
Automations complete tasks based on defined limits. AI learns tasks based on defined data. This is where algorithms come in. An algorithm is a process or set of rules to be followed in calculations or other problem-solving operations. Not so different sounding from an automation, right? The AI portion is the freedom within the algorithm to learn and adapt to a specific user or consumer based on their actions and personal data decisions.
It sounds smart, but it can get pretty sticky.
A classic writing exercise for third-graders is to write a set of instructions for making a peanut butter and jelly sandwich.
Sounds simple? Well, AI might interpret that as: spread peanut butter on a slice of rye bread using a pickle, spread jelly on a slice of banana bread 30 miles away using your hand, and put the slices of bread together, sticky sides out, and carry it around forever because you forgot a step 4 to put the sandwich on a plate.
According to Janelle Shane in her book “You Look Like a Thing and I Love You”, “The danger of AI is not that it’s too smart but that it’s not smart enough”.
We have a long way to go before AI is terrifying, but we are at the point where we can teach it to be useful, and even to be creative. And the workforce benefits are exciting.
In 2018, an MIT Task Force on the Work of the Future was commissioned by MIT president L. Rafael Reif. It analyzes the relationship between technology and the workplace for various professions at varying levels in the book “The Work of the Future: Building Better Jobs in an Age of Intelligent Machines,” written by MIT professors David Autor, David Mindell and principal research scientist Elisabeth Reynolds.
From a work perspective, specialized AI systems tend to be task-oriented; that is, they execute limited sets of tasks, more than the full set of activities constituting an occupation. Still, all occupations have some exposure. For example, reading radiographs is a key part of radiologists’ jobs, but just one of the dozens of tasks they perform. AI in this case can allow doctors to spend more time on other tasks, such as conducting physical examinations or developing customized treatment plans.
Single-task jobs – if they are the right jobs – can completely redefine workflow and change how we perform and how we allocate time. During the pandemic, we saw a significant rise in use for remote health apps and services which employ this type of AI to help analyze data with repetitive processes to help prioritize high-risk patients.
Simple jobs can yield complex results. Simple text can be interpreted to create detailed images. AI is dense, and it takes everything literally. What presents as highly intellectual creativity (like in the art image above) is really a logical process called diffusion where the AI uses patterns, and adapts patterns to achieve accurate results based on the text.
The most impressive part about AI right now, is that humans have the technology and the knowledge to teach a computer to think in basic terms. And that generates an inspiring future.
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