April 17, 2018
April 17, 2018
Contributor: Christy Pettey
AI requires CIOs to create and foster a data-literate society.
Given the pervasive nature of artificial intelligence (AI), the consequences of IT getting AI right or wrong are potentially profound. When used incorrectly, AI can unintentionally reinforce harmful biases, increase polarization and result in other damaging consequences.
“With the excitement for and hype surrounding the possibilities of AI, it is easy to focus on the technology and coding disciplines — what might considered the ‘artificial’ aspects,” says Alan D. Duncan, research vice president at Gartner.
“However, what could be thought of as the ‘intelligent’ aspects of a digitally connected world don't function — don't exist — without data. While conversant in the people, process and technology capabilities of business models, most executives and business and IT professionals do not ‘speak data’ fluently,” added Duncan.
To use AI accurately, companies need to build the case for data literacy as a new core competency for both creators and consumers of AI. Gartner advises CIOs responsible for enabling AI initiatives to follow three steps: First, build AI right, then use AI right and ultimately keep AI right.
To “build AI right,” it is key to first establish the basic vocabulary of AI — a technical dialect of how people “speak data.” At the very least, CIOs should determine the primary terms used when describing an AI system or solution, including the purpose or reason that the AI solution is being developed, as well as other key terms, such as the types of data used and gathered from the solution.
“Data is one of the cornerstones of any AI process, along with models and algorithms,” explains Duncan. “AI consumes and produces data. CIOs and data and analytics leaders will be responsible for developing and adhering to the data management aspects of AI. Building data management expertise along the full process with be key to success.”
Learn more: “Gartner Keynote: Do You Speak Data?”
The information language barrier can exist locally or systemically, regardless of program scope or organizational maturity. Addressing it requires a mindset shift as well as deliberate acknowledgment and intervention to course correct. To make data literacy more explicit, CIOs should develop a data literacy program.
Not even the most successful companies can afford to think they are immune to ethical mishaps. Extensive and explicit discussion is needed to distinguish between the types of ethical questions and dilemmas one can face versus the actual ethical position one can take.
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Recommended resources for Gartner clients*:
Artificial Intelligence Demands That CIOs Foster a Data-Literate Society
Fostering Data Literacy and Information as a Second Language
*Note that some documents may not be available to all Gartner clients.