When Stanley Kubrick’s 2001: A Space Odyssey hit the big screen in 1968, moviegoers shifted uncomfortably in their seats as a spaceship’s onboard computer named HAL-9000 refused an astronaut’s command, making the executive decision not to open the pod bay door. Artificial intelligence (AI) was pure science fiction back then. Today it’s reality — pervasive even.
“This is the future,” says Dr. Banks Odole, Academic Chair, Data Portfolio and Artificial Intelligence with SAIT’s School for Advanced Digital Technology (SADT). “One way or another, AI is going to change our lives. For each of us, how much of a change depends on our awareness of AI tools and how ready we are to begin using them.”
Robotics and automation. Machine learning. Natural language processing. Neural networks. The growing expanse of computer capabilities is at once fantastic and mind boggling. Data scientists are spurred on by the untapped potential of it all and, along with the rest of us, grapple over what it all might mean for the future of humanity.
“AI is new and we’re all just learning,” says Odole. “A lot of people are nervous about it.” There are so many unknowns. Will AI take over my job? How will it affect my business? What about my right to privacy? What happens if computers take over everything?
And here’s another reasonable question: if AI is the little red-eyed monster in the room, stoically watching us, listening in, feeding on human data, deconstructing our identities while steadily, stealthily burrowing into our unconscious to predict our next moves and systematically take over our jobs, our lives, the world — why on earth are we even entertaining it? The Roombas and Alexas, the cookies, the calorie counting, motion tracking, 24-hour, 360-degree wi-fi-enabled watchers — why do we invite them in?
Because they serve us.
“AI is a compilation of people’s intelligence. We are all contributing to this bucket [of data] that artificial intelligence is making use of.”
Making the most of AI — everywhere
With this qualified help, multiple book chapters can be reviewed simultaneously. It used to take you three days to review a book; now it will take a whole lot less. Your clients — the authors — continue to be happy. The boss is thrilled.
Then a handful of the 100 helpers use recent global experience to recommend a new payment system to speed up your accounts payable process.
“AI will continue to go into the data pool and make suggestions for improvements,” Odole says. But because collecting personal banking information from the clients introduces additional exposures on behalf of the company, your employer must decide whether the benefit outweighs the risk.
“At the end of the day, there’s still a person controlling whether the suggestion will be implemented.”
The data dilemma
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Prompt: data lake and scenery in binary code style, pink and orange |
Who is in control is possibly the most critical question in all of this. As long as we can say with confidence that AI works for us, and not the other way around, we’ll be more apt to embrace it as a tool. And beyond that, we all need to be aware of who developed the tool, and with what agenda or bias. There are ethical concerns, and there can be risk.
“AI is a compilation of people’s intelligence,” Odole says. “We are all contributing to this bucket [of data] that artificial intelligence is making use of.”
How that data — especially personal data — is collected, stored and analyzed raises concerns about privacy, particularly when it is collected without explicit consent, like those ads that pop up on your screen shortly after you mention a product in private conversation. “That information [the ad] is not injurious to me. It’s for my benefit,” says Odole. It smarts because it feels invasive, but it’s harmless.
It can be a different story when the exposure involves intellectual property or proprietary information like banking or your competitive business strategy. Downloading an app that records and transcribes meeting minutes — or uploading organizational documents into a generative AI public platform like ChatGPT and asking it to build out a business plan — could have you inadvertently sharing trade secret with who knows who.
“The moment you feed details into an AI model and ask for responses, you’ve given up that intellectual property,” says Bradley Ackroyd, Project Coordinator with SAIT’s Continuing Education and Professional Studies (CEPS). “Your information is now built and baked into the model.”
These are the kinds of things people need to be aware of before they choose and use AI tools, but Ackroyd assures us that we will all eventually choose to use them.
“AI as a tool is going to enhance as opposed to replace,” Ackroyd says. It can help us reach more informed decisions, make more accurate predictions and work more efficiently on more value-added tasks. It will advance the bottom line for organizations and companies that employ it — and increase the value of the people within them who leverage it.
To use or not to use is NOT the question.
It's, how?
For those worried about learning to leverage AI in their mid- to late careers — don’t be.
“AI has become a new general-purpose skillset,” says Ackroyd.
Both Ackroyd and Odole liken the introduction of AI to the first personal computers and cellphones: the best way to get started with AI is to start using it. Look for AI tools geared to your industry or role and experiment with them. Test AI’s possibilities while bearing in mind its limitations and risks.
“You don’t have to be a technical expert. You just need a broad-scoped understanding of the space where you can understand the art of the possible.”
Not entirely sure what that means? I went to AI for insight. While writing this story in August, I turned to the OpenAI tool ChatGPT, inserting the prompt:
PROMPT: Define "the art of the possible" in one sentence. 
: "The art of the possible" is the ability to achieve realistic and practical outcomes by navigating constraints and making the most of available opportunities.
ChatGPT, an acronym for Generative Pre-trained Transformer, is large language model-generative AI. Drawing from its massive stockpile of aggregated data (“Basically the entire Internet is contained in the model,” says Ackroyd), it delivers written output on whatever you ask for. You can request something as simple as a basic dictionary definition, or as detailed as a robust health and safety program based on best practices for your industry. AI will respond to your query (called a “prompt”) quite literally, which makes it important to be strategic in your ask — a skill known as prompt engineering. If you are unhappy with the response generated, refine your prompt to elicit better quality output.
PROMPT: Define "the art of the possible" in one sentence using plain language. : "The art of the possible" means finding practical solutions that work within the limits of a situation.
“You can actually have ChatGPT adopt different personas and make it more precise,” says Ackroyd. “You just need to push it down pathways."
PROMPT: Define "the art of the possible" in one sentence and with an Irish accent. : "The art o' the possible" is figurin' out what ye can actually get done with the resources ya got, within the limits ya face.
ChatGPT technology, like much of AI, is something anyone can use with relative ease. And it can be a powerful tool in terms of productivity, especially for tasks that may not be your core strength, like business writing.
“It fulfils a great need,” says Ackroyd. People just have to be mindful of possible risks — think intellectual property exposure — and potential ethical issues such as plagiarism.
“We can’t abdicate the need to think critically on the inputs that feed into data-driven decisions,” says Ackroyd. “We need to be able to push back and question the model and the validity. To eyeball the output and determine, based on our own experience and knowledge, if the model is delivering something that is reasonable or realistic.”
Critical thinking skills are, in many ways, more important than ever.
Developing the skills
Igor Cornejo worked as an automations and controls technician prior to enrolling in SAIT’s Digital Transformation Bootcamp in Applied Machine Learning. With his engineering background, he had been interested in learning more about AI for a while, but didn’t really know where to start.
“There’s a lot of information out there but you don’t really know what to believe and what not to believe,” says Cornejo. “I saw the bootcamp as an opportunity to get structured learning from data scientists. It established a baseline for me so now I can understand the different concepts and move forward.”
In his case, moving forward means a pivot from the engineering paradigm of tried, tested and true, to the dynamic frontier of AI where data is the basis for decisions that drive innovation.
“I’m now in agriculture, working in analytics AI as a machine learning specialist.” He’s using machine learning to make predictions farmers can use based on what happened in the past — everything from crop yields and soil requirements for fertilizer and irrigation, to expected insurance premiums and ideal harvest schedules.
“The first myth the instructors dispelled in the SAIT bootcamp was that you have to be a data scientist to use machine learning,” says Cornejo. You don’t have to know how to build the tool to use it.
“It’s like the difference between the instrument maker and the musician. There may be shared knowledge of music theory, but the two roles require completely different skill sets.”
It actually makes sense to think of AI as a musical instrument. As with any instrument, you have to invest some effort to reap the rewards. Pick it up respectfully and slowly start playing around. Do this repeatedly to build confidence. The more you practice, the more proficient you’ll become with its use. Eventually you could even be a star.
Austin Cooper (ITCS ’23) is an IT professional currently enrolled in SAIT’s Integrated Artificial Intelligence certificate program. His specialty is on the infrastructure side of things, such as data centre administration and computer virtualization. With a long-standing interest in the idea of “systems that can learn things for us,” he sees this kind of specialized AI certification as an opportunity.
“If I can add the data analysis side of things on top of my IT infrastructure knowledge and experience, it puts me in a better position professionally,” says Cooper. “When my CEO signals they want to move into AI, I’ll be able to say I understand AI technologies. Instead of just saying, ‘I’ll look into it,’ I can come up with a plan for the company.”
It’s empowering to anticipate change and prepare yourself for a major transformation.
“These tools aren’t set in stone,” says Cooper. “Unlike the previous things I’ve studied where there’s been decades and decades of best practices, industry standards and all that stuff — we’re at the forefront of artificial intelligence. It’s a very interesting dynamic. A wild frontier.”
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Prompt: AI as a musical instrument in a wild frontier setting — sci-fi cover concept art |
There truly is a lot here to be excited about. There’s tremendous opportunity in every sector, be that in building or employing AI tools themselves, or behind the scenes, conducting the extensive research, participating in the deliberation and debate, developing the international rules of engagement, or providing the ongoing oversight that wide-spread AI use requires.
AI has untold potential both to solve problems and to create them. To advance and safeguard the human condition or to erode it. As data science advances, it may get more and more difficult to differentiate between artificial intelligence and our own.
As long as AI continues to serve us, it’s all good.
Algorithm: a set of rules or instructions given to a computer to help it learn how to perform a task on its own.
Automation: the use of technology to perform tasks without human intervention.
Bias: in AI, bias refers to a systematic error in the data or algorithm that leads to incorrect or unfair outcomes.
Big Data: extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations.
Chatbot: a customer service software application used to conduct an online chat conversation via text or text-to-speech, in place of providing direct contact with a live human agent.
Data Science: a multidisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Ethics in AI: the study of moral principles and how they apply to the development and use of AI technologies.
Prompt: a phrase or individual keywords used as input for GenAI
Prompt Chaining: an approach that uses multiple prompts to refine a request made by a model.
View an extensive glossary of AI terms from expert.ai.
Editor's Note: Adobe Firefly is designed to be safe for commercial use. The current Firefly generative AI models were trained on a dataset of licensed content, such as Adobe Stock, and public domain content where copyright has expired.
Prompt for feature image: The red dot computer from 2001 Space Odyssey in a web of wires.
Oki, Âba wathtech, Danit'ada, Tawnshi, Hello.
SAIT is located on the traditional territories of the Niitsitapi (Blackfoot) and the people of Treaty 7 which includes the Siksika, the Piikani, the Kainai, the Tsuut’ina and the Îyârhe Nakoda of Bearspaw, Chiniki and Goodstoney.
We are situated in an area the Blackfoot tribes traditionally called Moh’kinsstis, where the Bow River meets the Elbow River. We now call it the city of Calgary, which is also home to the Métis Nation of Alberta.