How To Become An AI All Star, A Guide For Non-Techies


This is Part II of a two-part series on getting up to speed in AI. This part will address the career and job needs of the non-technical worker: the AI user. Part one addressed the technical worker: the AI developer. I ’ve published more than 40 articles, columns, blogs, and posts on artificial intelligence in the last year alone, covering general AI topics, components of AI, the business of AI, the ethics of AI, and the case for getting an early jump on AI. One thing we know: AI is the biggest transformation in history and will, within 12 to 18 months, change everything, including itself. Therefore, this is not a “nice to have.” It’s a “must have.”

OK, but how do I get there?

Learning AI with little or no prior experience will be a challenge, to be sure, so I enlisted the help of six experts. We sat down to answer one question: How does one become an AI all star? Here’s the panel’s step-by-step guide. Non-technical today, techie yesterday.

[Note: In the interest of impartiality, objectivity, and transparency, I am refraining from listing on-line sources by name. I’m sure you’ll have no trouble finding them.]

PREREQUISITES

1. Understand the Basics.

An old French country recipe for rabbit stew begins: “First you must catch the rabbit.” Same thing here. Begin by gaining a high-level understanding of what AI is and how it applies to the real world. Get onto a MOOC (massive open online courses) platform and find an Intro to AI course. There’s plenty of credible content in newspapers, journals, and podcasts. Great stuff here, too. Make sure you go after the non-technical stuff.

2. Learn How AI Is Shaping and Changing the World.

Take a “AI in Business” course. Explore the societal, employment, ethical, and governance implications of AI. See how AI is changing everyday life, including yours.

3. Find Non-Technical Roles.

Decide which non-technical roles within AI appeal to your interests and skill sets. AI ethics is the 800-pound gorilla; also of importance are finance, marketing, business management, international affairs, project management, and user experience (UX).

4. Learn the Basics of Data.

Become familiar with the sanctity of good data and the threat of data bias. Understand what’s involved with data collection, data labeling, and – of increasing importance – data privacy.

5. Get Fux on AI in Business.

Study how AI is – and will be – used in business: operations, logistics, huma resources, marketing, customer service, and critical decision-making. Focus on the strategic aspects of integrating AI into organizations.

6. Develop Expertise Using AI Tools for Non-Techies.

AI platforms and tools designed for non-technical users – automated machine learning (AutoML) and AI-powered analytics tools. – will play big roles in data analysis and strategic planning..

7. AI Ethics and Governance.

This will be – actually, already is – the most consequential aspect of AI. Develop a deep understanding of AI ethics, bias, and governance, andof the primary importance of this self-regulatory discipline. Responsible AI development and deployment is of critical concern.

ONGOING, CONTINUOUS LEARNING

8. Collaborate.

Connect with professionals in AI through LinkedIn, other communities of practice, ethics forums, and industry events. Collaborate with techies in a multidisciplinary way.

9. Stay Updated.

The pace of change has accelerated but the pace of change in AI is beyond imagination. Read regularly, read widely and read critically. Bookmark your preferred podcasts.

10. Embrace AI for Social Change.

AI can and should be used for social good and humanitarian purposes. That means, among other things, learning about AI initiatives to solving global challenges like climate change, healthcare, poverty, and education.

11. Regulation Is Not a 4-letter word.

More than any other advancement, AI needs to be regulated, but not at the coast of progress. Figuring out that balance will be the challenge of all challenges.

12. Go for the Non-Technical AI Jobs.

As high-tech as AI is, the non-techie will have as much to say about how it develops at the techie will. So, look for job openings in AI-related fields that match your non-technical skills and interests. There are plenty of open AI jobs: AI operations, AI project manager, AI strategist, AI policy analyst. And there will be more.

13. Continuous Learning.

AI is already the most rapidly evolving field, so there is no choice. Either stay with it or fall off it. The choice is entirely yours.

14. Network.

Networking is, always has been, and always will be the most effective career advancement strategy. The advice is the same to the non-techie as it is to the techie.

Remember that AI roles and opportunities beyond technical development are as key as those in the tech sphere. Non-techies can contribute significantly to the world of and with AI by understanding its broader foundation, ethical issues, and application in every domain. But this will not be a quick fix. As Henry Wadsworth Longfellow advised in his poem, The Ladder of St. Augustine,

“The heights by great men reached and kept

Were not achieved by sudden flight;

But they, while their companions slept,

Were toiling upward in the night.”



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