Evening reflections on the importance of story telling

If you want to scale beyond your own physical efforts, you will need to be able to convince others the importance of what you are doing. When you are successful at that you will be able to elicit their muscles to work for your own cause.

To be able to elicit their muscles, you will need to be able to tell a good story. If you read the book titled “Sapiens” by Yuval Harari, story telling is a technological innovation by the human species that has enabled large numbers of people to coordinate their efforts based around a single endeavor. It is one of the main causes for the human species’ predominance in our environment.

This innovation is enabled by our limbic brain which understands things based on narratives. Compelling narratives elicit an emotional response resulting in human motivation and corresponding action.

As a product manager working on the core product as opposed to growth, the primary focus is the narrative as opposed to the metrics.

The primary job of the executive is to “fight” for resources to further his agenda. The way he does so is by telling a compelling narrative to the company.

As opposed to a demagog, a good product manager tells a story, backs it up with data and delivers his promise. The demagog gets his resources by telling a story but never delivers anything of substance.

Learn to tell a story. That is a very important skill set acquire if you haven’t done so.

Inspired by conversations with Ved.

Related readings

Key take aways from “Gut Feelings”

  • Gut feelings definition
    • appears quickly in consciousness
    • underlying reasons we are not fully aware of
    • strong enough to act upon
  • Laws in the real world are different from those in the logical idealized world
  • Benjamin Franklin’s Moral Algebra
    • when in doubt weigh out the pros and cons of each side by cancelling out the pros that might weigh the same
  • Our brain
    • adaptive forgetting: data is destroyed with the aggregation of information into actionable insights
    • We can only decipher the output generated by our brain (a neural network) but cannot decipher the series of logical steps taken to derive this output
    • Deliberate thinking about reasons seems to lead to decisions that make us less happy
    • Thinking too much can slow down and disrupt performance
      • The gaze heuristics for catching baseball
    • the more complex a species the longer the period of infancy
    • The short term memory rule of 7 +/- 2
    • Intelligence means making bets, taking risk seeing more than what the eye sees
  • Satisfisers versus Maximizers
    • former is reported to be more optimistic, higher self-esteem and life satisfaction
  • Rule: Create scarcity and develop systematically
    • is a viable alternative in human and organizational development
  • Less is more
    • Stock picking of familiar stocks (partial ignorance) still out perform complex analysis (extensive knowledge)
  • Man and his environment
    • Herbert Simon: A man, viewed as a behaving system, is quite simple. The apparent complexity of his behavior over time is largely a reflection of the complexity in the environment he finds himself
    •  Steve Jobs, structured work place to maximize chance conversations
    • In an uncertain environment good intuitions must ignore information
    • Quality heuristics: we equate recognition to quality – Goldstein and Gigerenzer, 2002
      • why marketing might work in short run despite shitting products
    • One-reason decision making – a short cut people use despite official guidelines
      • implies a fast and frugal decision tree

References

  • Simple rules for a complex world, Epstein

Book Summary: The driver in the driverless car

Conditions the presage the leap into the future in any specific economic segment or type of service

  • Systemic requisite:
    • Widespread dissatisfaction – latent or overt with the status quo
  • Technology requisite:
    • Moore’s Law
      • Cheap computers
      • Cheap sensors – IOT
      • increase in Connection speed
      • Hand hosted AI
    • IOT
      • software
      • data connectivity
      • Handheld computing
    • Artificial Intelligence and Automation
      • Shift of discrete analog task into networked digital one

Five paradigms of computing

  • Electromechanical
  • Relay
  • Vaccuum tube
  • Discrete transistor
  • Integrated circuits – Moores’ Law

Current Concerns

  • Speed of technology evolution versus  speed of regulation – codified ethics
  • Equality, Risks and Dependency versus Autonomy
    • Does the technology have the potential to benefit everyone?
    • What are the risk and rewards?
    • Does the technology more strongly promote autonomy or dependence?
      • cheap software based technologies inexpensively scaled to reach millions-billions
      • the more revenue generated the more motivated developers would want to share it broadly

Future Concerns

  • Biometric theft
  • Merging of humans with computers
  • Extent of Gene alteration that is socially acceptable – new class of humans differentiated by genetic differences
    • mitigating health risk
    • higher intelligence
    • better looks
    • greater strength
  • Privacy will be a thing of the pass
  • Navigating technology trends as a navigator instead of a passenger
  • Large scale drone attacks

Artificial Intelligence

  • Definition: a cheap reliable industrial grade digital smartness running behind everything, Kevin Kelly, Editor of WIRED magazine
  •  Types
    • Narrow AI
    • Strong/General AI
      • Watson
  • Impact of existing human occupations
    • Doctors in health care
    • Lawyers

Education

  • Ancient Greece:
    • Socratic process whereby teacher guided students through the learning process by asking them questions
    • Education was privilege reserved for the elites
  • Middle Ages/Renaissance
    • Remained a priviledge
    • process of learning became more rote
    • more memorization
  • Online Education
    • Example: Khan academy
    • Researchers found people most likely to take advantage of online courses were those who need the least help
    • LA Unified: giving each student a tablet failed to move the needle
  • Minimally invasive Education, Mitra, New Delhi
    • NIIT building, Kalkaji slums
    • Key component of the learning process was the group dynamic
    • Self taught scholars learned as quick as school-bound peers
  • Self directed learning – flipped model of education
    • teacher no longer broadcast information, write lesson plans or stand in front of classes lecturing
    • teachers became coaches and guides to students needing additional help
    • students consumed recorded lectures or videos online at their own pace and in their own time
    • Teachers focus on judgment, nuances and emotional intelligence

Mores law and poverty

  • Comparatively poorer parts of the world will be able to leap frog into more modern and efficient era
    • wireless mobile phones
    • drones for deliver
    • Solar energy power plants
    • driver less cars
      • no need for traffic lights
      • freeways
      • Parking spaces
  • USA has no monopoly on innovation

Driver less Cars

  • Access versus ownership
  • Baidu, Google, Tesla
  • China
    • Bejing, Wuhu and Anhui
  • Singapore
  • city layouts become more flexible
  • commuting is less a hassle

Current trends

  • Plasma based water purification technology: kills 100% of bacteria and viruses
  • Energy

Further readings

  • How to create a mind: the secret of human thought revealed, Ray Krurzweil
  • The inevitable, Kevin Kelly
  • The internet of things: Mapping the value beyond Hype, McKinsey Global Institute
  • Infinite Resource: The Power of Ideas on Finite Planet
  • Abundance: The future is better than you think, Peter Diamandis

Deep learning and Machine Learning resources

A compiled list of sites that are useful for learning about fundamentals of artificial intelligence from a coders perspective:

Deep learning

  • http://course.fast.ai/lessons/lesson1.html –
    • Utilizes a breadth first approach through teaching
    • Focus on code first
    • Human learning flourishes when operating in different context.
  • http://yerevann.com/a-guide-to-deep-learning/

Machine Learning

  • https://www.analyticsvidhya.com/blog/2015/08/common-machine-learning-algorithms/
  • http://machinelearningmastery.com/naive-bayes-classifier-scratch-python/

Business Applications

  • https://medium.com/@thoszymkowiak/120-machine-learning-business-ideas-from-the-new-mckinsey-report-b81b239f336