
Leadership by Algorithm
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Content
- Intro
- Contents
- Praise for Leadership by Algorithm
- Prologue
- Chapter 1: Entering a New Era
- The rise of algorithms in organizations
- Automation and innovation
- Us versus them?
- Why we think about replacing humans
- When innovating becomes leading
- Do limits exist for self-learning machines?
- Chapter 2: The Leadership Challenge in the Algorithm Age
- Will your boss be a robot?
- The red-hot business model
- Human sophistication
- Chapter 3: Leading by Algorithm: Rushing In
- Being wise, not smart
- The leadership of today will not be the leadership of tomorrow
- Are we ready to accept?
- Who qualifies?
- Will others follow?
- The black-box problem
- Trusting algorithms
- Chapter 4: Management Controls, Leadership Conquers
- The art of running an organization
- Hooray for the administrator
- The problem with too many managers
- Why your mindset matters
- Achieving more means less management
- The danger of status-quo thinking
- Targets make you blind to what really matters
- Any leaders out there?
- Leadership is not management
- Not all hierarchy is algorithmic
- Chapter 5: Bridging Management and Algorithms
- Do I need to become a coder?
- Does human intuition pay off?
- The human brain shines, the algorithm gets things done
- Bring out the blockchain
- Management by algorithm
- The limits of management by algorithm
- Co-operation is the key word
- Chapter 6: Algorithms and Leadership
- Why leadership needs to be the real deal
- Looking ahead with a sense of purpose
- It's all about connecting with others, stupid!
- Failure happens
- what matters is, can we correct it?
- Does it make any sense?
- On the fabric of sense-making
- Critical thinking
- Curiosity
- Agility
- Imagination
- Creativity
- Emotional intelligence
- Empathy
- Ethical judgment
- Conclusion
- Chapter 7: The Day that Empowerment Changed
- Empowerment makes the world go round
- Leadership empowers humans
- Why aversive?
- Tackle the fear
- Tackle loss of control
- It's all about power
- Create transparency
- Continuous education
- How to explain?
- Leadership empowers algorithms
- The art of delegation
- Purpose makes for data
- Chapter 8: Co-Creation as a New Beginning?
- Iron Man as the example to follow?
- Co-operating in the new diversity
- To be an orchestral conductor
- Initiating co-operation
- Creating added value
- Chapter 9: The Art of Leadership: Purpose and Inclusion
- Know your context
- On the importance of purpose
- Visionary leadership
- How to develop your visionary abilities?
- Ethical leadership
- Reducing the complexity of ethics
- Augmenting ethics through automation
- How to develop your ethical leadership abilities?
- Summary: The benefits of purpose-driven leadership
- Setting priorities to look at data
- Framing the right kind of questions for the right kind of strategy
- Providing a focus on how to analyze the data
- Helping to integrate new business demands with the values of the organization to create relevant and valuable strategies
- Explaining clearly why data is collected and analyzed
- On the importance of inclusive leadership
- Connecting leadership
- How to develop your connecting abilities
- Trustworthy leadership
- Trust building starts with the leader
- The art of fostering trust
- How to develop your trustworthiness
- Diversity-minded leadership
- The diversity curator
- Experiment and fail
- How to develop your diversity mindset
- Humble leadership
- Please challenge me!
- Promoting bottom-up thinking
- How to develop your humility?
- Summary: The benefits of inclusive leadership
- Different departments to co-operate
- Integrating teams of data scientists in the daily operations of the company
- Promoting transparency in communication and exchange of data
- Empower algorithms in non-biased ways
- Be humble, and work on being tech savvy
- Chapter 10: What Will Be and What Should Be
- Too good to be true?
- The end user is technology, or am I wrong?
- What about the human?
- We will survive. again!
- Co-operation above all
- How to move on
- Building the right culture
- Humans lead, algorithms manage
- Who knows where to go?
- Continuous education
- Humanity in AI as a guiding tool
- Tolerance for imperfection
- Conclusion
- Publishing details
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