Mike Walsh

The Algorithmic Leader

How to Be Smart When Machines Are Smarter Than You

• Gebundenes Buch

Produktbeschreibung

The greatest threat we face is not robots replacing us, but our reluctance to reinvent ourselves. We live in an age of wonder: cars that drive themselves, devices that anticipate our needs, and robots capable of everything from advanced manufacturing to complex surgery. Automation, algorithms, and AI will transform every facet of daily life, but are we prepared for what that means for the future of work, leadership, and creativity? While many already fear that robots will take their jobs, rapid advancements in machine intelligence raise a far more important question: what is the true potential of human intelligence in the twenty-first century? Futurist and global nomad Mike Walsh has synthesized years of research and interviews with some of the world's top business leaders, AI pioneers and data scientists into a set of 10 principles about what it takes to succeed in the algorithmic age. Across disparate cultures, industries, and timescales, Walsh brings to life the history and future of ideas like probabilistic thinking, machine learning, digital ethics, disruptive innovation, and de-centralized organizations as a foundation for a radically new approach to making decisions, solving problems, and leading people. The Algorithmic Leader offers a hopeful and practical guide for leaders of all types, and organizations of all sizes, to survive and thrive in this era of unprecedented change. By applying Walsh's 10 core principles, readers will be able to design their own journey of personal transformation, harness the power of algorithms, and chart a clear path ahead-for their company, their team, and themselves.

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Produktdetails

• Verlag: Page Two Books, Inc.
• Seitenzahl: 256
• Erscheinungstermin: 12. März 2019
• Englisch
• Abmessung: 236mm x 163mm x 32mm
• Gewicht: 553g
• ISBN-13: 9781989025338
• ISBN-10: 1989025331
• Artikelnr.: 53545286

Autorenporträt

Mike Walsh

Inhaltsangabe

#0 - Introduction: Welcome to the algorithmic age#0.1: Flying the
unfriendly skies
#0.2: A tale of two leaders
#0.3: The leader in the rhizome
#0.4: The end of all jobs?
#0.5: How to read this book
Part I: Change Your Mind
#1 - Work backwards from the future
#1.1: Start with algorithms
#1.2: Understand what machines can do
#1.3: Build for your future customers
#1.4: Learn from your kids
#1.5: Focus on experiences, not devices
#2 - Aim for 10X not 10%
#2.1: Focus on multiples, not margins
#2.2: Don't let a great idea hold you back from a better one
#2.3: Learn to follow the data
#2.4: Unlock the value of your own knowledge
#2.5: Imagine a future without your company in it
#3 - Think computationally
#3.1: Start with first principles
#3.2: Think like a computer
#3.3: Augment your intelligence
#3.4: Learn to trust the algorithm
#3.5 Speak the languages of power
#4 - Embrace uncertainty
#4.1: See the world like a gambler
#4.2: Rethink the role of meetings
#4.3: Conduct a decision audit
#4.4: Build an algorithmic brain trust
#4.5: Experiment to find questions, not answers
Part II: Change Your Work
#5 - Make culture your operating system
#5.1: Put principles before processes
#5.2: Be a gardener, not a prison guard
#5.3: Design teams to succeed
#5.4: Set the stage for smart ideas
#5.5: Use data to hack your culture
#6 - Don't work, design work
#6.1: Challenge your raison d'être
#6.2: Find the scaled-up solution
#6.3: Preserve your talent patterns
#6.4: Let your team own the work
#6.5: Build a digital twin
#7 - Automate and elevate
#7.1: Find the new job inside the old one
#7.2: Re-train, re-equip, and re-energize
#7.3: Create a team to rethink teams
#7.4: Reimagine, don't just replace work
#7.5: Focus on the exceptions
Part III: Change Your World
#8 - If the answer is X, ask Y
#8.1: Pick the right moral compass
#8.2: Avoid automating bias
#8.3: Understand the explainability trade-off
#8.4: Pick the right target
#8.5: Focus on the forest
#9 - When in doubt, ask a human
#9.1: Humanize, don't standardize
#9.2: Look outside the window
#9.3: Solve for everyone, not for the few
#9.4: See the world as a designer
#9.5: Augment relationships, don't replace them
#10. Solve for purpose, not just profit
#10.1: Connect people to their work
#10.2: Beware the algorithmic inequality trap
#10.3: Use algorithmic management thoughtfully
#10.4: Build platforms that you would use yourself
#10.5: Transform work by transforming yourself
Epilogue
Acknowledgements
References and further reading