Talking to Computers

Predicting the Future

Forecasting and scenario planning try to predict future by using data and wisdom from the past. Predicting the business climate of the future allows organizations to make changes to their current strategy. Any business that fails to adapt to changes is guaranteed to fail. Understanding the current disrupting forces and future market demands will enable an organization to innovate better. Royal Dutch/Shell used scenario planning during oil crisis to understand forces that were causing the disruption and how it should adapt for the future (Ramirez, et. al., 2002). Scenario planning is one of the strategies that could be used by businesses to predict plausible futures, best and worst-case future scenarios or the optimal situation that should be created in the future. Scenario planning uses iterative sessions to extract knowledge from diverse set of induvial from an organization to predict the future.

Talking to Computers

            Twenty six years ago, Nicholas Negroponte, director of MIT's Media Lab, in an email to Wired, predicted that in another 15 years human beings will be talking to the computers instead of using graphical interfaces. The speech recognition technology was in its infancy in 1994 but Negroponte was envisioning about not sitting right in front of a computer but talking to it like a human being. Back in 1994 Negroponte was able to understand the forces that would impact the future of speech recognition. The intonations used in a human conversation could express different feelings like sarcasm, compassion, exasperation, etc. Negroponte suggested that technology should be sophisticated enough to understand human emotions in speech. With advancement in algorithms, machine learning and AI, today, computers can understand human feelings much better than 26 years ago. Another force that impacted successful recognition of speech was the number of words that could be successfully stored in the memory of the computer. With advancement in computer processing speed, memory, internet, cloud computing, machine learning and AI, speech recognition has become a reality. Today we can use applications like Siri and Alexa and speak to computers, from a distance just like Negroponte envisioned twenty six years ago.

References

Ramírez R., Churchhouse S., Palermo A, Hoffmann J. (2020). Using Scenario Planning to Reshape Strategy. MIT Sloan Management Review.

Negroponte N. (1994). Talking to Computers: Time for a New Perspective. Retrieved from https://www.wired.com/1994/02/negroponte-9/

 

  

Forecasting Vs Scenario Planning

Forecasting

            Forecasting is the act of predicting future by using past data. For centuries we have been forecasting events like travel time, weather, duration to complete a construction project, etc.. Complexities of forecasting can vary from simple fairy tales to well formulated statistical predictive models. Forecasting allows us to make decisions without absolutely knowing the future. Castel, et. al. (2019) suggest four characteristics that are essential for any forecasting instrument – (a) there are regularities to be captured; (b) those regularities are informative about the future; (c) the proposed method captures such regularities; yet (d) excludes distorting non-regularities (noise). Forecasting models use past regularities in the data to understand the effect of different factors on the outcome. 

Scenario Planning

            When the future is uncertain and the current norms are disrupted by unforeseen circumstances, scenario planning might provide a method to chart the future. Scenario planning was used heavily during world war II and helped Royal Dutch/Shell company during oil crisis. Some scenario planning approaches try to predict the best case and worst-case scenarios while others try to present the most optimal state that should be created in the future (Ramírez et. al., 2020). Oxford scenario planning method, as per Ramírez et. al. (2020),  “by recognizing the part of uncertainty that is unpredictable and by actively exploring the sources of the turbulence and uncertainty, the goal is to iteratively and interactively generate new knowledge and insights to help organizations perceive their circumstances”. Scenario planning uses all levels of expertise within an organization to brainstorm and understand how future might be reshaped by current events. During scenario planning, multiple iterations are conducted to generate new knowledge and plausible future scenarios.

Advantages and Disadvantage of Forecasting and Scenario Planning

            Both forecasting and scenario planning try to foresee the future with the understanding of past events. Statistical forecasting uses systematic analysis of data to understand causal relationship between influential factors. Systematic analysis of past data using statistical forecasting models provide a repetitive and a reproducible analytical pattern. Statistical forecasting models try to eliminate bias by focusing on the data than opinions. On the other hand, scenario planning uses the knowledge and intuition of multiple individuals. When future is changing drastically from the past, statistical forecasting will not be able to predict future. It requires human intuition. Also, when data about the past is not available, statistical models will not perform well. Scenario planning, because of the expertise of individuals involved in the discussion, could perform better even when some of the data from the past is not available. At the same time, scenario planning could introduce tunnel vision and prevent individuals to confront all plausible future scenarios.

References

Castel, J. L., Clements, M. P., & Hendry, D. F. (2019). Forecasting: An essential introduction. New Haven: Yale University Press

Ramírez R., Churchhouse S., Palermo A, Hoffmann J. (2020). Using Scenario Planning to Reshape Strategy. MIT Sloan Management Review.

 

Accidental Inventions

            A number of scientific discoveries appear to happen purely thru luck. Invention of sticky notes, Febreze, saccharin (artificial sweetener), x-ray, pacemaker, etc. appear to be accidental. But, Louis Pasteur, the famous French biologist, famously said “in the field of observation chance favors only the prepared mind”. In this blog we will see that the history of the invention of penicillin and graphene prove that chance does not favor everyone but, at times, it seems to favor the prepared mind.

Penicillin – The Miracle Drug

            As early as 15th century, Paracelsus was able to explain normal function of human being and diseases in terms of chemical synthesis and pioneered drug discoveries. But, even at the turn of the 20^th century the chemical that would kill a microorganism and leave the host unaltered was not discovered (Rifkind & Freeman, 2005). Paul Ehrlich was able to discover the magic bullet for treating syphilis around 1910 but the search for more magic bullets remain futile (Lagerkvist, 2003).

            In 1928, Alexander Fleming, a Scottish bacteriologist working in St. Mary’s Medical School in London, was studying staphylococcus. He left a culture plate open on his desk and went on a vacation. When he returned from vacation, while talking to a friend, noticed a zone around the invading fungus on the culture plate in which the bacteria did not grow. He found that an air borne fungus, which is closely related to the mold that grows in bread, has fallen into the culture plate. Alexander Fleming obtained an extract from the mold and called it penicillin (Gaynes, 2017). Alexander Fleming found the synthesis of penicillin to be very hard, but the world war II increased the demand for a drug that would heal the infection of soldiers. It took more than 10 years since the day of its original discovery to create a process to isolate penicillin from broth culture (Rifkind & Freeman, 2005).

Graphene – The Miracle Material

            Graphene, the material that could revolutionize biomedical, technology, transportation, energy, etc. was discovered when two scientists at the University of Manchester when they were playing about with flakes of carbon graphite (Conner, 2013, Nanographi., n.d.). Geim and Novoselov were using the sticky tape to remove some flakes from a pile of graphite and found that some flakes were thinner than others. By repeatedly peeling off layers from the pile of graphite, they managed to separate the thinnest layer of the material that is one atom thick. The one atom thick material is graphene and is found to be useful from solar cells to alcohol distillation to dialysis. In an interview with Steve Conner of Independent, the co-inventor and Nobel laureate Novoselov, said “a playful idea is perfect to start things but then you need a really good scientific intuition that your playful experiment will lead to something, or it will stay as a joke forever” (Conner, 2013). 

            Though it could appear as if Geim and Novoselov invented graphene by chance, a deeper look at their approach would reveal that there is a method to the madness. They both frequently held 'Friday night experiments' where they tried new and different experiments that is not related to their day job. They also had a playful approach to conducting research. It was during one of these Friday night experiments, while playfully removing layers of graphite they discovered graphene (Conner, 2013). Just like Louis Pasteur noted chance favors the prepared mind and Geim and Novoselov were prepared to capitalize on the opportunity that chance provided them.  

References

Rifkind, D., & Freeman, G. L. (2005). The nobel prize winning discoveries in infectious diseases. San Diego: Elsevier Science & Technology.

Lagerkvist, U. (2003). Pioneers of microbiology and the nobel prize. Singapore: World Scientific Publishing Co. Pte. Ltd.

Gaynes R. (2017). The discovery of penicillin - new insights after more than 75 years of clinical use. Emerging Infectious Disease. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5403050/#R2

Nanographi. (n.d.). 60 uses of graphene. Retrieved from https://nanografi.com/blog/60-uses-of-graphene/

Conner S. (2013). The graphene story: how Andrei Geim and Kostya Novoselov hit on a scientific breakthrough that changed the world... by playing with sticky tape.  Retrieved from https://www.independent.co.uk/news/science/graphene-story-how-andrei-geim-and-kostya-novoselov-hit-scientific-breakthrough-changed-world-playing-sticky-tape-8539743.html

Dream Big (Data) - Introduction

 In near future, Big data and new innovative ideas will transform our society in ways we have only dreamed before. With advancements in Internet of Things (IoTs), genetics, wearable devices, smart home technologies, etc. huge volume of data is generated. This deluge of data provides us with a great opportunity to improve the well being of our society. For example, insurance companies will be able collect all data about a person - health history, hobbies, personal and professional activities, all properties owned, online behavior, etc. and provide coverage for all risks that he or she faces. Cities will be able to collect and synthesize data to control traffic patterns, deploy first responders, control pandemics, etc. Big data also pose several privacy and security challenges (Slade, 2020). When used carelessly, it could hurt rather than help our society.

Futuring and Innovation is one of the courses at Colorado Technical University as part of my doctoral studies in big data. As part of the curriculum we are encouraged to innovate and dream big on the possibilities that are in front of us. I will be using this blog to dream big and post my innovative ideas on the use of big data. 

References

Blogger. (n.d.). Retrieved from http://www.blogger.com

Slade, R. (2020). I [Love|Hate] Big Data. ISSA Journal, 18(11), 7.