Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
The Hidden Risks of AI Securities, Privacy, Ethics, Innovation, and Market Stability: How to Anticipate AI Risks, Protect Investments, and Prevent Dis

The Hidden Risks of AI Securities, Privacy, Ethics, Innovation, and Market Stability: How to Anticipate AI Risks, Protect Investments, and Prevent Dis

Sunn, Stephan S.

Paperback

Business GeneralManagement

Currently unavailable to order

ISBN13: 9798171183172
Publisher: Independently Published
Pages: 58
Weight: 0.18
Height: 0.15 Width: 6.00 Depth: 9.00
Language: English
The Hidden Risks of AI: Securities, Privacy, Ethics, Innovation addresses the critical gap between rapid enterprise technology adoption and effective risk governance. Unlike traditional IT projects, artificial intelligence introduces layered vulnerabilities-spanning direct operational biases, second-order market manipulations, and systemic contagion. The book establishes a distinct financial market perspective, framing issues like algorithmic trading, deepfakes, and opaque data pipelines not as mere technical glitches, but as severe liabilities capable of erasing corporate valuation and threatening market stability overnight.

What sets this work apart is its pragmatic approach to the hidden costs of scaling intelligent systems. The text introduces the concept of AI Debt-compounding risks across governance, data, trust, and physical infrastructure-and demonstrates how ethics washing and unmonitored black box models expose firms to catastrophic regulatory fines and class-action litigation. It moves beyond theoretical debate by offering actionable toolkits, including the 10-Question Privacy Stress Test, the TEVV (Test, Evaluate, Verify, Validate) framework, and stress-testing protocols designed to prepare organizations for cross-border compliance regimes like the EU AI Act, SEC mandates, and global privacy laws.

In today's volatile economic landscape, where massive capital expenditures collide with emerging threats like agentic AI, this book provides essential guidance for executives, board members, and business leaders. It emphasizes that human governance, organizational culture, and proactive compliance must act as the primary controls against automation bias and workslop. By translating complex AI vulnerabilities into clear financial, legal, and operational terms, the book proves that mastering AI governance is no longer a restrictive handbrake, but a vital strategic differentiator for long-term enterprise value.

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