『AI for Analogs』のカバーアート

AI for Analogs

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AI for Analogs

著者: David Schippers
ナレーター: Scott Sundberg
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Amazonプライム会員限定、プレミアムプラン 3か月間無料体験キャンペーン開催中。4か月目以降は月額1,500円で自動更新します。いつでも退会できます。2026年7月15日(水)まで。

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You did not grow up with AI. You need to grow into it.

From a teenager in a jean jacket in the 1980s to a Doctor of Science with two decades at the intersection of cybersecurity, business, and academic leadership, Dr. David Schippers has lived every transition the Analog generation has faced. Paper to screens. Manual systems to automation. Stable routines to relentless reinvention. He didn't grow up with AI either. He grew into it - and now he is showing you how.

AI for Analogs is not written for engineers, coders, or digital natives who have been swimming in technology since childhood. It is written for people who built real careers before AI showed up, survived digital disruption, and now find themselves staring at one more seismic shift and wondering how to make sense of it.

Dr. Schippers breaks down what AI is, what it is not, what matters, and what does not - and shows how to use it without surrendering your judgment, your experience, or your identity.

What you'll learn.

  • AI explained in plain English - what it is, what it isn't, and what actually matters.
  • The five-part prompting formula - the single most-cited practical artifact from early readers.
  • The Analog Advantage - why your experience is the foundation, not the obstacle.
  • AI safety and data hygiene - protect what you've built without shutting out the tools.
  • Amplified Intelligence - how humans and AI work as a team without surrendering judgment.

Validated by the readers it was written for

"AI for Analogs is THE handbook you need to get comfortable and build your confidence using AI." - M. Farkas, CEO, Public Relations Firm

"AI doesn't just make you more efficient. It reveals what kind of thinker you are." - L. Stradley, Chief Privacy Officer, Financial Services

©2026 David Schippers (P)2026 David Schippers
コンピュータサイエンス 個人的成功 出世 意思決定・問題解決 機械理論・人工知能 自己啓発
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