Serendipity, Errors and Exaptation

Dr. Aly, O.
Computer Science

Introduction: The purpose of this discussion is to discuss and analyze three terms: Serendipity, Errors, and Exaptation. The discussion begins with some basic definitions, followed with some examples for each term.

Serendipity: As indicated in (De Bonte & Fletcher, 2014), Serendipity can happen anytime anywhere. It can happen through a flyer, or a new perspective or new insight from people you talk to which can provide new ideas hidden in your mind. The new perspective can provide unexpected inspiration. The key factor is to be open to new opportunities, new ideas and ignore the fear that is associated with these new opportunities and ideas as they can lead to discovering an innovation. In (Copeland, 2017), the term Serendipity is used to describe discovery in science which happens at the intersection of opportunity and wisdom.

In (Crampton, 2017; Holubar, 1991), the term Serendipity was coined by Horace Walpole (1717-1797) in 1754 in allusion to an ancient oriental legend of the “Three Princes of Serendip.” Serendip is an old name for the country known today as Sri Lanka (Crampton, 2017). The story described how three traveling princes made discoveries about things that they did not plan to explore or that supposed them during their travel (Crampton, 2017). Thus, Walpole created the word “Serendipity” to indicate and refer to the accidental discoveries (Crampton, 2017). The term “Serendipity” today can mean the ability to make discoveries not intentionally or purposely searched for, and the greater the knowledge, the more likely the discovery (Holubar, 1991). It also infers to a happy and unexpected event which happen due to the chance when searching for something (Crampton, 2017).

There are several serendipitous discoveries in science such as Penicillium which was discovered to make the Penicillin. This serendipitous discovery happened in 1928 by Alexander Fleming, when he found a clear area around the mold (Crampton, 2017). Instead of ignoring the clear area, he investigated and found out that the mold was making an antibiotic which killed the bacteria around it. He identified the mold as Penicillium and named the antibiotic as Penicillin (Crampton, 2017).

Exaptation: Exaptation is defined in (Bonifati, 2013) as a result of a process through which an initial attribution of new functionality to existing outcomes leads to new outcomes. Exaptation is also known as “Pre-Adaptation” (Feltrinelli & Del Garda, 2009). Although Exaptation is regarded to be the most important evolutionary technique in the history of species, technologies, and ecosystems, it is yet little studied and largely unknown outside the field of evolutionary biology (Feltrinelli & Del Garda, 2009). Darwin proposed the “Pre-adaptation” as the solution to explain how gradual process such as natural selection can evolve complex organs whose fitness contribution become positive only when the organ is complete (Feltrinelli & Del Garda, 2009). The term of “Pre-adaptation” is expanded by Gould and Vrba, as cited in (Bonifati, 2013; Feltrinelli & Del Garda, 2009), and coined the term with “Exaptation” for a non-natural selection-driven evolutionary process (Feltrinelli & Del Garda, 2009). In (Gould & Vrba, 1982), the “Exaptation” was proposed for the operation of useful character which is not built by selection for its current role as an effect but evolved for other usages and later “co-opted” for their current role (Gould & Vrba, 1982). Exaptation is described as a central concept in several fields such as technological change, and evolutionary biology (Feltrinelli & Del Garda, 2009). As cited in (Feltrinelli & Del Garda, 2009), Stuart Kauffman states that Exaptation “is one of the most creative forces in the eco- and techno-sphere” (Feltrinelli & Del Garda, 2009).

Examples of Exaptation include the feathers and flight-sequential exaptation in the evolution of birds whose original purpose was to regulate temperature, but over time they were used to aid flight (Barve & Wagner, 2013; Gould & Vrba, 1982; Kastelle, 2010). Another example is the lens crystallins, which are a light-refracting protein which originated as enzymes (Barve & Wagner, 2013). Another example of Exaptation is the phonograph to which Edison attributed the functionality of serving as a dictating machine. However, Edison specified nine other possible uses of the phonograph in a published article in 1878 (Bonifati, 2013). Within the context of technology, Exaptation can suggest that businesses can accumulate technological knowledge without anticipation of its subsequent usage (Andriani & Cattani, 2016). Moreover, Exaptation can emerge from processes through which an initial attribution of new functionalities to existing artifacts or organizations can lead to new artifacts and eventually to new markets in the socio-economic innovation processes (Bonifati, 2013).

Error: The historical and technological records contain various and numerous examples of innovation (Buchanan, 2013). Some of these innovations were by mistake. Examples of the past business mistakes which proved to be brilliant include personal copiers, selling via pet stores, ATMs, credit card for students, organic food, and more.

References

Andriani, P., & Cattani, G. (2016). Exaptation as source of creativity, innovation, and diversity: introduction to the Special Section. Industrial and Corporate Change, 25(1), 115-131.

Barve, A., & Wagner, A. (2013). A latent capacity for evolutionary innovation through exaptation in metabolic systems. Nature, 500(7461), 203.

Bonifati, G. (2013). Exaptation and Emerging Degeneracy In Innovation Process. Economics of Innovation and New Technology, 22(1), 1-21.

Buchanan, B. (2013). Alex Mesoudi, Kevin N. Laland, Robert Boyd, Briggs Buchanan, Emma Flynn, Robert N. McCauley, Jürgen Renn, Victoria Reyes-García, Stephen Shennan, Dietrich Stout, and Claudio Tennie. Cultural Evolution: Society, Technology, Language, and Religion, 193.

Copeland, S. (2017). On serendipity in science: discovery at the intersection of chance and wisdom. Synthese, 1-22.

Crampton, L. (2017). Serendipity: The Role of Chance in Making Scientific Discoveries. Retrieved from https://owlcation.com/stem/Serendipity-The-Role-of-Chance-in-Making-Scientific-Discoveries.

De Bonte, A., & Fletcher, D. (2014). Scenario-Focused Engineering: A toolbox for innovation and customer-centricity: Microsoft Press.

Feltrinelli, P., & Del Garda, G. (2009). Exaptation as a Source of Innovation, Creativity, and Diversity in Evolutionary Sciences.

Gould, S. J., & Vrba, E. S. (1982). Exaptation-A Missing Term in the Science of Form Paleobiology, 8(1), 4-15.

Holubar, K. (1991). Serendipity–its basis and importance.

Kastelle, T. (2010). Innovation Through Exaptation. Retrieved from http://timkastelle.org/blog/2010/05/innovation-through-exaptation/

Case Study: The Impact of Relying only on Standard Forecasting instead of Using Proper Scenario Planning

Dr. Aly, O,
Computer Science

Introduction

Scenario planning first emerged for application to businesses in a company set up for researching new forms of weapons technology in the RAND Corporation (Chermack, Lynham, & Ruona, 2001). Kahn of RAND corporation pioneered a technique titled “future-now” thinking (Chermack et al., 2001). Scenario planning encourages organizational leaders to think the unthinkable (Chermack et al., 2001). It has been identified as a useful means of conducting strategic organization planning (Chermack et al., 2001). With a focus on long-term and short-term future, scenario planning forces the organizational planners to consider paradigms which challenge their current thinking (Chermack et al., 2001).

In (Wade, 2012), scenario planning is described as a productive, creative, and existing way to develop the groundwork for a strategic plan which does not bet the future on the company on a single most likely scenario. Scenario planning challenges the idea of a single future but an array of possible future which could potentially unfold (Wade, 2012). The outcome of the scenario planning process is a portfolio of future scenarios, each of which represents a different way the business landscape could look in a few years, and not just the landscape, but also the players who involve in the business such as competitors, suppliers, customers, employees and other stakeholders (Wade, 2012). Scenario planning is considered to be a critical tool for anyone who is not just managing, but also leading (Wade, 2012). It enables the leader to create a realistic vision for the future and craft the strategies which will make the leader successful (Wade, 2012).

The good scenario planning goes beyond just high-low projections (Schoemaker, 1991). In (Peterson, Cumming, & Carpenter, 2003), scenario planning is described as a systematic method for thinking creatively about possible complex and uncertain futures. The underlying concept of the scenario planning is to consider a variety of possible futures which include many of the important uncertainties in the system instead of focusing on accurate prediction of a single outcome (Peterson et al., 2003). There are many approaches to scenario planning such qualitative approach,

The applications of scenario planning can be organized by their use of qualitative or quantitative methods and their approach toward the uncertainty (Peterson et al., 2003). Most scenario planning incorporates both qualitative and quantitative details, and the relative mix of these two aspects distinguish different scenarios exercises (Peterson et al., 2003). Some scenario planning is intended to facilitate the management uncertainty, while others are used to discover it (Peterson et al., 2003). Three examples of scenarios which have been used to approach problems which were beyond the read of the traditional predictive methods include “Shell Oil,” “Monte Fleur, South Africa,” and “Northern Highland Lake District, Wisconsin” (Peterson et al., 2003). In the Shell Oil, the traditional forecasting was found inappropriate, and scenario planning was used to allow well-defined actor “Shell” with a clear goal to maximize shareholder value to develop a strategy for an uncertain future (Peterson et al., 2003). In Monte Fleur, scenario planning is used by bringing a group of disconnected people with divergent goals together to create a shared understanding of the uncertainties surrounding the transition to democracy (Peterson et al., 2003). In Northern Highland Lake District in Wisconson, a team of scientists created an initial set of scenarios to begin a scenario-planning process among a broad group of stakeholders (Peterson et al., 2003). These examples demonstrate that scenario planning can be modified in a multitude of ways to fit a particular context (Peterson et al., 2003).

Scenario Planning Could Have Saved Blockbuster

Blockbuster is a very good example of the business which did not do the proper scenario-type planning and only relied on standard forecasting. Blockbuster Inc. was an American-based DVD and video game rental service. It was founded by David Cook, who used his experience with managing large database networks as the foundation for the retail distribution model of the Blockbuster (Albarran, 2013). In 2009, Blockbuster had an estimated 7,100 retail stores in the US with additional locations in 17 countries worldwide, and had over 60,000 employees in the US and worldwide (Albarran, 2013). The headquarter of the company was in McKinney, Texas (Albarran, 2013). Blockbuster filed for bankruptcy just prior its 25^th anniversary on September 22, 2010, and on April 11, Blockbuster was acquired by satellite television service provider Dish Network at an auction price of $233 million and the assumption of $87 million in liabilities and other obligations (Albarran, 2013).

The innovation is not about developing new products, but it is about reinventing business process and building entirely new markets to meet untapped customer needs (Albarran, 2013). For some businesses, innovation is deliberative and planned, while for others innovation is the direct result of a triggering event such as a change in external market conditions or internal performance which forces a change in business strategy (Gershon). Three main types of innovations: product innovation, process innovation, and business model innovation. Blockbuster followed the traditional forecasting model without paying attention to any innovation and the impact of the technology on its business. If Blockbuster had implemented scenario-typed planning in their Business Process, it would not have failed. The Blockbuster retail model was going to be difficult to sustain in the presence of advancing technology (Albarran, 2013). Figure 1 illustrates a Scenario Planning Model.

Figure 1: Scenario Planning Model

Forces Driving Blockbuster Out of Business

The Internet made the future of e-commerce and “disruptive technologies” possible. Netflix is one of these “disruptive technologies” which took the form of a unique business process innovation (Albarran, 2013). Netflix is an online subscription-based DVD rental service founded by Reed Hastings in 1997during the emergent days of electronic commerce (EC) when companies like Amazon and Dell Computer were starting to gain prominence (Albarran, 2013). Netflix provides greater value to the consumer when compared to the traditional video rental store which charges by the individual DVD rental unit, by offering two to three DVDs per week for a fixed monthly price (Albarran, 2013). Moreover, Netflix offers greater convenience in the form of “no late fee.” (Albarran, 2013). The success of Netflix is the direct result of personalized marketing which involves knowing more about the particular interest and viewing habits of the customers (Albarran, 2013). Netflix utilizes the power of the Internet to promote a proprietary software recommendation system (Albarran, 2013). This recommendation system solved the common complaints with Blockbuster when renting an unfamiliar movie, and the customer gets dissatisfied with the viewing experience later. With this recommendation system, Netflix offers suggestions of other films that the customer might like based on the past selection and the brief evaluation filled by the customers (Albarran, 2013).

Blockbuster failed to react to the competition and revise its business model (Albarran, 2013). Blockbuster could have re-position itself strategically as early as 2011 (Albarran, 2013). However, Blockbuster could have acquired Netflix or modified its strategy by duplicating many of the same EC efficiencies which Netflix’s business model had already demonstrated (Albarran, 2013). Blockbuster chose to ignore the competitive threat posed by Netflix.

Scenario Planning could have saved Blockbuster. Scenario Planning offers a framework for resilient conservation policies when faced with uncontrollable, irreducible uncertainty (Peterson et al., 2003). Scenario Planning consists of using a few contrasting scenarios to explore the uncertainty surrounding the future consequences of a decision. Blockbuster could have benefitted from a few contrasting scenarios to explore the uncertainty that is resulted from the competition, the technology, and the presence of the Internet and e-Commerce. The key benefit of the Scenario Planning process is that it reveals different ways of the future based on which more flexible and more thoughtful and better decision can be made today (Wade, 2012). An additional benefit of scenario planning includes the increased understanding of key uncertainties, the incorporation of alternative perspectives into conservation planning, and greater resilience of decisions to surprise (Peterson et al., 2003).

In summary, the traditional forecast model did not help Blockbuster stay in business. On the contrary, the traditional forecast model did not forecast the future of Blockbuster. The forces such as the Internet, the emerging technologies supporting e-commerce, recommendation systems for customers, monthly rental for two to three DVDs, and no late fee have driven Blockbuster out of business. Blockbuster could have saved itself if it has applied scenario planning strategically to protect itself from the uncertainty of the future, instead of following the same traditional forecasting model which worked perfectly in the past but became not applicable any longer in the presence of the Internet and other emerging technologies and innovations driven by these technologies.

References

Albarran, A. B. (2013). Media management and economics research in a transmedia environment: Routledge.

Chermack, T. J., Lynham, S. A., & Ruona, W. E. (2001). A review of scenario planning literature. Futures Research Quarterly, 17(2), 7-32.

Gershon, R. A. MEDIA INNOVATION: Disruptive Technology and the Challenges of Business Reinvention: Kalamazoo, Western Michigan University.

Peterson, G. D., Cumming, G. S., & Carpenter, S. R. (2003). Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology, 17(2), 358-366.

Schoemaker, P. J. H. (1991). When and How to Use Scenario Planning: A Heuristic Approach with Illustration. Journal of Forecasting, 10(6), 549-564.

Wade, W. (2012). Scenario planning: A field guide to the future: John Wiley & Sons.

Concepts of Forecasting and Predictions

Dr. Aly, O.
Computer Science

Purpose:

The purpose of this discussion is to research the concepts of forecasting and predictions in a business or innovation context. The discussion will identify and document one infamous prediction that actually came true.

Discussion

Prediction: The goal of prediction is to obtain a significant estimate of what the value of the dependent variable will be by known independent variable value (Bateh & Heyliger, 2014). However, as indicated in (Garrett, 2013), the prediction is rough and is subject to a large error of the estimate. Prediction means different things to different technical disciplines and different people (Peterson, Cumming, & Carpenter, 2003). The prediction is understood to be the best possible estimate of future conditions (Peterson et al., 2003). The less sensitive the prediction is to drivers the better (Peterson et al., 2003). Whereas scientists understand that predictions are probabilistic conditional statements, non-scientists often understand them as things that will happen no matter what they do (Peterson et al., 2003).

The historical and technological records contain various and numerous examples of predictions that came true (Dreher, n.d.; Sterbenz, 2013). Some of these predictions that came true include the following as indicated in (Dreher, n.d.; Sterbenz, 2013).

Jules Verne predicted a man on the moon in 1865.
Ray Bradbury foretold earbuds in 1953.
Edward Bellamy envisaged the debit card in 1888.
Robert Boyle predicted organ transplants in the 1660s.
Arthur C. Clark imagined the iPad in 1968.
Nikola Tesla predicted personal wireless devices in 1909.
H. G. Wells predicted the atomic bomb in 1914.
Roger Ebert predicted video-on-demand services Netflix and Hulu in 1987.
Isaac Asimov predicted the use of the Internet for learning in 1988.

For this discussion, the focus is on the prediction of Nikola Tesla for the personal wireless devices in 1909.

Nikola Tesla’s Prediction of Personal Wireless Devices in 1909: In 1891, Nikola Tesla developed a type of resonant transformer called the Tesla coil, which achieved a major breakthrough in his work by transmitting 100 million volts of electric power wirelessly over a distance of 26 miles to light up a bank of 200 light bulbs and run one electric motor (Bhutkar & Sapre, 2009). Tesla claimed to have achieved 95% efficiency, but the technology had to be shelved because the effects of transmitting such high voltages in electric arcs would have been disastrous to humans and electrical equipment in the vicinity (Bhutkar & Sapre, 2009). This technology has been neglected in obscurity for several years. However, the advent of portable devices such as mobiles, laptops, smartphones, MP3 players brought this technology into life and Tesla’s prediction of the wireless in 1909, which came true.

Tesla was called as a visionary as well as “charlatan” (Lumpkins, 2014). However, many attest that his early vision of alternating current transmission systems and wireless power were the precursors of today’s energy-harvesting technology (Lumpkins, 2014). He is regarded as a prolific inventor (Marincic, 1982). Tesla believed that by transmitting waves of alternating radio-frequency (RF) energy, devices such as electric vehicles and even flying dirigibles, could reuse this energy for consistent operation (Lumpkins, 2014). Tesla experimented with large-scale wireless power distribution by building the world’s first power station in Long Island, New York (Xie, Shi, Hou, & Lou, 2013). He planned to use the power station called Wardenclyffe Tower to transmit not only signals but also wireless electricity (Xie et al., 2013). However, due to its large electric fields, which significantly diminished the power transfer efficiency, Tesla’s invention was not successful and was never put into practical use (Xie et al., 2013).

The field of wireless power has been growing over the past sixty years, from conceptual ideas such as collecting solar power in space and “beaming” it back to Earth-based collectors, like a Dyson sphere, to the reality of charging Philips Sonicare electric toothbrush with an inductive charger (Lumpkins, 2014). The impact of the Tesla’s innovation and prediction is observed in every minute of our lives.

References

Bateh, J., & Heyliger, W. (2014). Academic Administrator Leadership Styles and the Impact on Faculty Job Satisfaction. Journal of leadership Education, 13(3).

Bhutkar, R., & Sapre, S. (2009). Wireless energy transfer using magnetic resonance. Paper presented at the Computer and Electrical Engineering, 2009. ICCEE’09. Second International Conference On.

Dreher, B. (n.d.). 9 Incredible Historical Predictions That Came True. Retrieved Jan 27, 2018, from https://www.rd.com/culture/historical-predictions-that-came-true/.

Garrett, M. (2013). Traditional Forecasting Leads to Traditional Results … Failure. Retrieved Jan 27, 2018, from https://www.forbes.com/sites/matthewgarrett/2013/08/22/traditional-forecasting-leads-to-traditional-results-failure/#4a0c95e0bebc, Forbes.

Lumpkins, W. (2014). Nikola Tesla’s Dream Realized: Wireless power energy harvesting. IEEE Consumer Electronics Magazine, 3(1), 39-42.

Marincic, A. (1982). Nikola Tesla and the wireless transmission of energy. IEEE Transactions on Power Apparatus and Systems(10), 4064-4068.

Peterson, G. D., Cumming, G. S., & Carpenter, S. R. (2003). Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology, 17(2), 358-366.

Sterbenz, C. (2013). 16 Of The Most Impressive Predictions Of All Time. Retrieved Jan 27, 2018, from http://www.businessinsider.com/predictions-from-the-past-that-came-true-2013-9.

Xie, L., Shi, Y., Hou, Y. T., & Lou, A. (2013). Wireless power transfer and applications to sensor networks. IEEE Wireless Communications, 20(4), 140-145.

Scenario Planning vs. Traditional Forecasting

Dr. Aly, O.
Computer Science

Purpose

The purpose of this discussion is to compare and contrast the concepts of scenario planning versus traditional forecasting.

Traditional Forecasting: A forecast is described as the best estimate of a particular method, model, or individual (Peterson, Cumming, & Carpenter, 2003). The view toward the forecast is that a forecast may or may not turn out to be true (Peterson et al., 2003). Forecast is uncertain (Peterson et al., 2003). Prediction, on the other hand, means different things to different technical disciplines and different people (Peterson et al., 2003). The prediction is understood to be the best possible estimate of future conditions (Peterson et al., 2003). Forecast and prediction are closely tied to the notion of optimal decision making (Peterson et al., 2003). The optimal decisions maximize the expected net benefits and minimize the expected net losses (Peterson et al., 2003).

Traditional forecasting has different models and methods as indicated in (DSG, 2011). The traditional forecasting methods involve trending, extrapolation and curve fitting methods, which are used when forecast time frame is short to medium term, and there is sufficient evidence that forecast inflection points do not exist in the time frame (DSG, 2011). It also involves the Adoption and Penetration Model which is used when there is sufficient evidence that the historical and forecast time frame of the model will include inflection points (DSG, 2011). The scope of these Adoption and Penetration Models is usually total market, and the objectives are to predict market penetration, the location of the inflection points, and take-up times (DSG, 2011). The traditional forecasting methods also include the “Casual and Multivariate” methods which are used when multiple known causal influences are driving or constraining the market (DSG, 2011). The two most common form of this approach include the Total Market models and the Market Share methods (DSG, 2011). Other traditional forecasting models include Time-Series Analysis, Agent-Based Models, and Trackers & Bottom-Up Models (DSG, 2011). As indicated in (Garrett, 2013), traditional forecasting leads to traditional results and may be failures. Thus, the models of the traditional forecasting do not have to be applied in every business scenarios.

Scenario Planning: Scenario planning first emerged for application to businesses in a company set up for researching new forms of weapons technology in the RAND Corporation (Chermack, Lynham, & Ruona, 2001). Kahn of RAND corporation pioneered a technique titled “future-now” thinking (Chermack et al., 2001).

Scenario planning encourages organizational leaders to think the unthinkable (Chermack et al., 2001). It has been identified as a useful means of conducting strategic organization planning (Chermack et al., 2001). With a focus on long-term and short-term future, scenario planning forces the organizational planners to consider paradigms which challenge their current thinking (Chermack et al., 2001).

As indicated in (Chermack et al., 2001), scenario planning has been defined in several ways. Scenario planning was defined as “an internally consistent view of what the future might turn out to be -not a forecast, but one possible future outcome.” Scenario planning is defined as “a tool for ordering one’s perceptions about alternative future environments in which one’s decisions might be played out” (Chermack et al., 2001). It was also defined as “that part of strategic planning which relates to the tools and technologies for managing the uncertainties of the future” (Chermack et al., 2001). The major themes of the scenario planning include history, scenarios as stories, the theory of scenarios, the effect of scenarios on decision-making capabilities, creating “future memory” from scenarios, scenarios as tools for organizational learning, and the evaluation of scenario projects (Chermack et al., 2001). Scenario planning offers a framework for developing more resilient conservation policies when confronted with uncontrollable, irreducible uncertainty (Peterson et al., 2003).

In (Wade, 2012), scenario planning is described as a productive, creative, and even existing way to develop the groundwork for a strategic plan which does not bet the future on the company on a single most likely scenario. Scenario planning challenges the idea of a single future but an array of possible future which could potentially unfold (Wade, 2012). The outcome of the scenario planning process is a portfolio of future scenarios, each of which represents a different way the business landscape could look in a few years, and not just the landscape, but also the players who involve in the business such as competitors, suppliers, customers, employees and other stakeholders (Wade, 2012). Scenario planning is considered to be a critical tool for anyone who is not just managing, but also leading (Wade, 2012). It enables the leader to create a realistic vision for the future and craft the strategies which will make the leader successful (Wade, 2012).

The good scenario planning goes beyond just high-low projections (Schoemaker, 1991). In (Peterson et al., 2003), scenario planning is described as a systematic method for thinking creatively about possible complex and uncertain futures. The underlying concept of the scenario planning is to consider a variety of possible futures which include many of the important uncertainties in the system instead of focusing on accurate prediction of a single outcome (Peterson et al., 2003). There are many approaches to scenario planning such qualitative approach,

There is no one-size-fits-all approach to scenario planning (Wade, 2012). Six steps are proposed by (Wade, 2012) as a general guideline for scenario planning. These six steps include: framing the challenge, gathering information, identifying the driving forces, defining the future’s critical uncertainties, generating the scenarios, and fleshing them out and creating storylines. Four more steps follow these six steps including the validation, the implication assessment, the identification of signposts, and the monitoring and updating the scenario as the time moves (Wade, 2012). In (Peterson et al., 2003), a similar guideline is provided. However, in (Peterson et al., 2003), the approach is described as a qualitative approach, presenting the process as a linear process, with iteration, where system assessment leads to a redefinition of the central question, and testing can reveal blind spots which require more assessment. The process begins with the identification of a focal issue, followed by the assessment, identification of alternative, building scenarios, testing scenarios, and policy screening (Peterson et al., 2003).

The key benefit of the scenario planning process is that it reveals different ways of the future based on which more flexible and more thoughtful and better decision can be made today (Wade, 2012). An additional benefit of scenario planning includes the increased understanding of key uncertainties, the incorporation of alternative perspectives into conservation planning, and greater resilience of decisions to surprise (Peterson et al., 2003).

References

Chermack, T. J., Lynham, S. A., & Ruona, W. E. (2001). A review of scenario planning literature. Futures Research Quarterly, 17(2), 7-32.

DSG. (2011). Traditional forecasting and modeling methods. Retrieved Jan 27, 2018, from http://www.danielresearchgroup.com/WhatWeDo/ForecastsandMarketModels/TraditionalForecasting.aspx, Daniel Research Group: Understanding the Future.

Peterson, G. D., Cumming, G. S., & Carpenter, S. R. (2003). Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology, 17(2), 358-366.

Schoemaker, P. J. H. (1991). When and How to Use Scenario Planning: A Heuristic Approach with Illustration. Journal of Forecasting, 10(6), 549-564.

Wade, W. (2012). Scenario planning: A field guide to the future: John Wiley & Sons.

Accidental Inventions and Game-Changing Ideas

Dr. Aly, O.
Computer Science

Innovation can refer to a successful novel variant, a novel variant, or any variant (Buchanan, 2013). It can also refer to the ideas underlying an invention or its first implementation (Buchanan, 2013). Innovation can also refer to both the process by which variants are generated and the product (Buchanan, 2013). Innovation introduces new cultural variation into the population through copying error, novel invention, refinement, recombination, and exaptation (Buchanan, 2013). Thus, innovation is not a synonym of variation, as the variation entails a broader category which encompasses diverse forms only some of which are novel (Buchanan, 2013).

Game-changing ideas are the “transformational magic” which takes the organizations from ordinary to exceptional (Myatt, 2012). Game changers focus on pursuing a game-changing idea (Myatt, 2012). They never get satisfied with the ordinary or mundane (Myatt, 2012). They are described as relentless, persistent, committed to pursuing that idea that is hunting them (Myatt, 2012). Moreover, the game changers are originals, and they refuse to allow their organizations to adopt conventional orthodoxy and bureaucracy (Myatt, 2012). They challenge the norm, break the conventions, and encourage diversity of thoughts (Myatt, 2012). They have a clear purpose, and they understand the value of serving something beyond themselves (Myatt, 2012). In (Myatt, 2012), six steps called SMARTS for finding and implementing game-changing ideas; Simple-Meaningful-Actionable-Relational-Transformational-Scalable (Myatt, 2012).

Every game-changing ideas and innovation have driving forces that either supported them or were against them. The driving force is described by (Wade, 2012) as “something with the potential to bring about significant change in the future.” Some of the driving forces include uncertainty, potential impact, stability, risks, benefits, culture (Wade, 2012).

The historical and technological records contain various and numerous examples of innovation (Buchanan, 2013). Some of these innovations were accidental. Some of these accidental inventions include the microwave, Saccharin, Slinky, Play-Doh, Super Glue, Teflon, Bakelite, Pacemaker, Velcro, X-Rays, Stainless Steel, Plastic, Teflon, Corn Flakes (Biddle, 2010; Cyran, 2012). The discussion in this project is limited to two of these accidental inventions, and the driving forces that supported them. The driving forces can be culture, religion, technical complexity, technology and so forth.

Pacemaker

In 1959, the engineer Wilson Greatbatch and the cardiologist Chardack developed the first fully implantable pacemaker (Haddad & Serdijn, 2009). The accidental innovation of the pacemaker happened when Greatbatch took 1-megaohm variety instead of picking a 10,000-ohm resistor out of a box to use on a heart-recording prototype (Biddle, 2010). The resulting circuit produced a signal which sounded for 1.8 milliseconds, and then paused for a second – a dead ringer for the human heart (Biddle, 2010). Greatbatch realized that the precise current of the resulting circuit could regulate a pulse, overriding the imperfect heartbeat of the person who has an issue with the heartbeat (Biddle, 2010). The pacemaker before this accidental innovation was large and was attached to the person from the outside. However, after this accidental innovation, the effect of the resulting circuit can lead to a small circuit which can be implanted into the person’s heart (Biddle, 2010). Pacemakers have become smaller and lighter over the years (Haddad & Serdijn, 2009).

The pacemaker evolved with time. The complexity and reliability in the modern pacemaker have increased because of the developments in the integrated circuit design (Haddad & Serdijn, 2009). For instance, the early pacemakers did not have the capability of electrogram sensing pacing the ventricles asynchronously (Haddad & Serdijn, 2009). However, the modern devices, called “demand mode pacemakers,” included a sense amplifier measuring cardiac activity, thereby avoiding competition between paced and intrinsic rhythms (Haddad & Serdijn, 2009). The demand pacemaker functional block involves power source, a sense amplifier, timing control, output driver, and electrode, while the earlier pacemaker functional block involved only power source, pulse generator and electrodes (Haddad & Serdijn, 2009).

Since pacing stimuli were only delivered when needed, longevity increase by the introduction of demand pacemakers (Haddad & Serdijn, 2009). In 1963, the pacemakers were introduced to have the capability to synchronize ventricular stimuli to a trial activation (Haddad & Serdijn, 2009). Since that time, the clinical, surgical and technological developments have proceeded at a significant pace providing the highly reliable, extensive therapeutic and diagnostic devices that are available today (Haddad & Serdijn, 2009). Today, the modern pacemaker technologies are extremely complex and include an analog part, comprising the sense amplifier and a pacing output state, and a digital part consisting of a microcontroller, and some memory, implementing diagnostic analysis of sensed electrograms, adaptive rate response and device programmability (Haddad & Serdijn, 2009).

X-Ray

In 1895, the German physicist Wilhelm Roentgen was performing a routine experiment involving cathode rays (Biddle, 2010; Cyran, 2012; NASA, n.d.). He observed that a piece of fluorescent cardboard was lighting up from across the room (Biddle, 2010; NASA, n.d.). A thick screen was placed between his cathode emitter and the radiated cardboard, demonstrating that particles of light passed through a solid object (Biddle, 2010). He discovered it through arms and hands created detailed images of the bones inside (NASA, n.d.). He experimented with cathode-ray tubes. Glass tubes with the air sucked out and a special gas pumped in (Cyran, 2012). When he ran the electricity through the gas, the tube would glow. However, something strange happened after he surrounded the tube with blackboard. When he turned on the machine, a chemical few feet away started to glow (Cyran, 2012). He was surprised because the cardboard should have prevented any light from escaping (Cyran, 2012). He found out that cathode-ray tube had been sending out more than just visible light (Cyran, 2012). It was sending out invisible rays which could pass right through paper, wood, and even skin (Cyran, 2012). He captured X-Ray images, and the first of the skeletal images was his wife’s hand (Biddle, 2010; Cyran, 2012; NASA, n.d.).

X-Rays have much higher energy and much shorter wavelength than the ultraviolet light. Scientists refer to X-Rays regarding their energy instead of their wavelength, because they have very small wavelengths, and some of them are no bigger than a single atom of many elements (NASA, n.d.). Due to the benefits of the X-Rays, they have been used in many domains such as dental, any part of our body, and even the universe (NASA, n.d.). In the area of radiography, X-Rays have used on dental, chest, mammography which is recommended for early detection of breast cancer. These tests utilize short bursts of X-Ray beams and post little risk (NRPB, n.d.). X-Rays benefit extended to fluoroscopy a technique that uses X-Rays to produce a moving image on a TV screen. More sophisticated method of using X-Rays is found in the computed tomography (CT) scan to produce 3-D pictures of the patients (NRPB, n.d.). Although X-Rays provided many benefits to our lives, they expose some risks as they are a form of electromagnetic radiation, just like light waves and radio waves (NRPB, n.d.). X-Rays can cause damage to cells in the body, which in turn can increase the risk of developing cancer with the increasing number of X-Rays tests (NRPB, n.d.).

In summary, game-changing ideas and innovation can also be accidental. The key success factor and forces for any innovation and game-changing ideas rely heavily on the person to process persistently, patiently, wisely with great commitment to go against the conventional and the traditional process and be bold. Game changer leaders have these common attributes which make them game changers, leaders, and innovators.

References

Biddle, S. (2010). Whoops! The 10 Greatest (Accidental) Inventions of All Time. Retrieved from https://gizmodo.com/5620910/whoops-the-10-greatest-accidental-inventions-of-all-time.

Cyran, P. (2012). The 20 Most Fascinating Accidental Inventions. Retrieved from https://www.csmonitor.com/Technology/2012/1005/The-20-most-fascinating-accidental-inventions/X-ray-images.

Haddad, S. A. P., & Serdijn, W. A. (2009). Ultra-low-power biomedical signal processing: an analog wavelet filter approach for pacemakers: Springer Science & Business Media.

Myatt, M. (2012). 6 Steps for Creating a Game Changer. Retrieved January 30, 2018, from https://www.forbes.com/sites/mikemyatt/2012/10/10/how-great-leaders-create-game-changers/#43ee8019558b, Forbes.

NASA. (n.d.). X-Rays. NASA, Retrieved January 30, 2018, from https://web.archive.org/web/20121122024930/http://missionscience.nasa.gov/ems/11_xrays.html.

NRPB. (n.d.). X-Rays – Benefits and Risks. National Radiological Protection Board, Retrieved January 30, 2018, from http://www.radiology.ie/wp-content/uploads/2012/01/X-Rays-Benefits-and-Risks.pdf.

Wade, W. (2012). Scenario planning: A field guide to the future: John Wiley & Sons.

Think Tank Methods

Dr. Aly, O.
Computer Science

Purpose

The purpose of this discussion is to research some of the think tank concepts and methods that are deliberate and foster innovation. The discussion will address some key points about each method.

Discussion

Think Tank is also known as “Reflection Pool” (Caliva & Scheier, 1992). It was developed to assist in addressing the needs to expand the process of thinking without restriction (Caliva & Scheier, 1992). The traditional way for solving problems and learning include conferences, workshops and so forth (Caliva & Scheier, 1992). However, with Think Tank, the techniques go beyond the traditional method to include simulating creativity in the field, developing holistic thinking patterns, providing powerful tools to deal with complex and long-term problems, challenging restlessly creative leaders, and renewing the participants’ spirit (Caliva & Scheier, 1992).

There is no consensus on the definition of the Think Tank, despite the considerable efforts of the academic literature to define Think Tank and to establish its topology (Kelstrup, n.d.). Think Tank is defined in various studies and journals. The term “Think Tank” is defined as a structure for a group that focuses on providing a solution to a particular problem in the technology and science domain (Caliva & Scheier, 1992). However, it is regarded as a process rather than a structure by (Caliva & Scheier, 1992). Thus, the term can be defined as “a process for in-depth consideration of issues and challenges whose relevance reaches beyond the individual or program and the immediate time frame.” (Caliva & Scheier, 1992). In (Shaw, Russell, Greenhalgh, & Korica, 2014), Think Thank is described as “a civil society organization specializing in the production and dissemination of knowledge related to public policy” (Shaw et al., 2014). In (Whittenhauer, n.d.), the Think Tank is described as “an organization that assembles experts with the sole purpose of coming together to think—more specifically, to think of ideas on how to solve a particular problem” (Whittenhauer, n.d.). In (Hauck, 2017) Think Tanks are described as “organizations that have to proliferate, playing more and more the role of very relevant actors on the political scene in clashes over interests, preferences, and ideas for the formation of public policies” (Hauck, 2017). In (Kelstrup, n.d.), Think Tanks are described as agents established globally in public policy across different levels of governance (Kelstrup, n.d.).

Some indicated that the first proliferation wave of Think Tanks began in the United States and the United Kingdom at the turn of the twenty century (Hauck, 2017). Most of the Think Tanks in the United States are funded by the government or political advocacy groups (Whittenhauer, n.d.). However, some of the Think Tank are established as for-profit organizations which sell their intellectual property or ideas to businesses and government (Whittenhauer, n.d.). In Western Europe, the government finances 75% of German Think Tanks, to include public organizations in the studies (Hauck, 2017). As indicated in (Shaw et al., 2014), around 6500 Think Tanks are operating across 169 countries and representing a range of organizations and interests (Shaw et al., 2014). The role of the Think Tanks is increasing in healthcare domain worldwide through the work of organizations such as “Commonwealth Fund” in the US, the King’s Fund in the UK, and the Health and Global Policy Institute in Japan. These organizations support health services research and policy analysis such as surveying trends in health coverage and communicating their work through media briefings and research seminars to shaping the health policy and planning (Shaw et al., 2014).

Two Major Concepts of Autonomous and Influence: The two major concepts of Think Tank are the autonomy and influence (Kelstrup, n.d.). These two concepts are drawn from existing literature on the definitions and description of the Think Tank (Kelstrup, n.d.). Thus, the general definition of Think Tank is “Organizations that claim autonomy from and attempt to influence public policy” (Kelstrup, n.d.). Based on these two underlying concepts, two dimensions are formed to include demand-driven and supply-driven (Kelstrup, n.d.). Two main perspectives are categorized under each of these two dimensions; “political policy world,” and “administrative policy world” (Kelstrup, n.d.). The “political policy world” perspective include two main sub-categories; the “political advisor” under the demand-driven dimension, and the “instrumental” under the supply-driven dimension (Kelstrup, n.d.). Under the “political advisor,” which is the demand-driven approach, Think Tank meet the demand for biased knowledge (Kelstrup, n.d.). Under the “instrumental,” which is the supply-driven approach, Think Tank supply normative knowledge by stakeholder interests (Kelstrup, n.d.). The “administrative policy world” perspective include two main sub-categories; the “administrative, institutional” and “network” (Kelstrup, n.d.). Using the “administrative institutional” that is the demand-driven approach, Think Tank meet the demand for cognitive knowledge (Kelstrup, n.d.). In the “network,” which is the supply-driven approach, Think Tank supply cognitive knowledge to public administration (Kelstrup, n.d.).

Two Major Models of “one roof” and “without roof”: There are two models for the Think Tank; the “one roof” Think Tank model and “without a roof” Think Tank model (Whittenhauer, n.d.). In the “one roof” Think Tank Model, the diversified group comes in one place “under one roof” and interacts together face to face (Whittenhauer, n.d.). Before the “one roof” model, the participants of the Think Tank communicated through phones and written correspondences (Whittenhauer, n.d.). The costs that are associated with “one roof” model such as travel was a factor in decreasing the interaction among the Think Tank members (Whittenhauer, n.d.). This model of “one roof” is regarded to be an effective Think Tank approach when immediate interactive conservation facilitates the intensified thought process (Whittenhauer, n.d.). In 2009, the second model of “without roof” Think Tank model is used by organizations which do not have to fund the “one roof” model (Whittenhauer, n.d.). The “without a roof” Think Tank model is more effective than the “one roof” because it does not require the funding that is required by the “one roof” on travel costs and so forth. The “without roof” Think Tank model spends most of the money on research and the required costs for computers and utilities are not paid by think tank organization using this model (Whittenhauer, n.d.).

Five Think Tank Techniques: In (Penttila, 2007), there are five Think Tank techniques that enhance innovation: “combine ideas,” “think backward,” “do rapid prototyping,” “Create an internal incubation fund,” and “take it online” (Penttila, 2007). Example of the “Combine Ideas” technique is the interactions between ideas and the methods to merge them which is used by Xerox (Penttila, 2007). Example of “Think Backward” technique is the innovation method of McDonald by “backcasting” the product to see the end product first and work towards that end product (Penttila, 2007). Example of “Do Rapid Prototyping” is McDonald which puts ideas through fast prototyping for a short period such as one day (Penttila, 2007). Example of the “Create an internal incubation fund” is Xerox which sets aside funds that encourage employees to network and chase ideas that otherwise would not have a budget (Penttila, 2007). For the “Take it online” Think Tank technique, as cited in (Penttila, 2007), Anthony Warren, the director of the Farrell Center for Corporate Innovation and Entrepreneurship at Penn State states that “Everybody can contribute all the time” (Penttila, 2007).

The Most Influential Think Tanks: In (TBS, 2015), there are fifty most influential Think Tanks in the United States. However, for this Discussion Board, the researcher is covering only the first five of these most influential Think Tanks in the United States. The first Think Tank in the US that has great influence is “Belfer Center for Science and International Affairs” established in 1973 to analyze arms control and nuclear threat reduction (TBS, 2015). The “Earth Institute” is the second influential Think Tank in US established in 1995 focusing on addressing important global issues such as sustainable development and the needs of the world’s poor (TBS, 2015). The third most influential Think Tank is “Heritage Foundation” established in 1973 (TBS, 2015). The focus of the Heritage Foundation is to track the yearly growth of federal spending, revenue, debt and deficit, and entitlement programs, which it then publishes as the Budget Chart Book and distributes free to the public. The fourth most influential Think Tank is “Human Rights Watch” established in 1978 with the goal to conduct research and advocacy on human rights (TBS, 2015). Kaiser Family Foundation is one of the first five most influential Think Tank founded in 1948 focusing on major health care issues in the US and the world (TBS, 2015).

References

Caliva, L., & Scheier, I. H. (1992). The Think Tank Techniques. Retrieved from http://academic.regis.edu/volunteer/ivan/sect03/sect03b.htm, The Center for Creative Community(Santa Fe, New Mexico).

Hauck, J. C. R. (2017). What are ‘Think Tanks’? Revisiting the Dilemma of the Definition *. Brazilian Political Science Review, 11(2), 1-30. doi:http://dx.doi.org/10.1590/1981-3821201700020006

Kelstrup, J. D. (n.d.). Four Think Tank Perspectives. Retrieved from http://www.lse.ac.uk/europeanInstitute/pdfs/Kelstrup_EILS.pdf.

Penttila, C. (2007). 5 Big Biz Think Tank Techniques. Retrieved from https://www.entrepreneur.com/article/174688.

Shaw, S., Russell, J., Greenhalgh, T., & Korica, M. (2014). Thinking about Think Tanks in Health Care: a call for a New Research Agenda.

TBS. (2015). The 50 Most Influential Think Tanks in the United States. The Best Schools: Retrieved from https://thebestschools.org/features/most-influential-think-tanks/.

Whittenhauer, K. (n.d.). Effective Think Tank Methods. Retrieved from http://classroom.synonym.com/effective-think-tank-methods-5728092.html.

Think Tank Methods

Dr. Aly, O.
Computer Science

Purpose

The purpose of this discussion is to discuss the research group decision-making methods. The discussion will include the Delphi technique, and at least two methods with a comparison among these methods.

Discussion

There are different techniques in group decision-making. These techniques include Brainstorming, Normal Group Technique, Delphi Method, Dialectical Inquiry (Sarkissian, 2002). The techniques in group decision-making also include the “Plop” Method” (Ozcan, Misir, & Kheiri, 2013; Schwartz, 1994), Decision by Authority Rule (Schwartz, 1994), Decision by Authority without Consultation (Minnesota, 2007), and Decision by Authority after Consultation (Minnesota, 2007). Moreover, the group decision-making techniques also include Average of Group Member Opinion (Minnesota, 2007), and Decision by Minority Rule (Minnesota, 2007; Schwartz, 1994). The decision by Majority Rule (Minnesota, 2007; Schwartz, 1994) also known as “Voting and Polling” (Schwartz, 1994), Decision by Experts (Minnesota, 2007), and Consensus (Minnesota, 2007) are also group decision-making techniques. The two group decision-making techniques for this DB are limited to the Delphi method, and to the Plop Method.

The Delphi method is described as “a general way of structuring the group communication process and making it effective enough to allow a group of individuals, functioning as a whole, to deal with complex problems (Saizarbitoria Iñaki, Arana Landín, & Casadesús Fa, 2006). It is also described as a systematic process attempting to obtain group consensus resulting in much more open and in-depth research as each member of the group has a unique contribution to identify a new aspect of the problem for more research (Saizarbitoria Iñaki et al., 2006). The Delphi method is also described as “a panel of experts is asked individually to provide forecasts in a technical field, with their views summarized and circulated for iterative forecasting until a consensus is reached” (Ritchie, Lewis, Nicholls, & Ormston, 2013). The Delphi method a commonly used technique for research in the fields of medicine or sociology (Saizarbitoria Iñaki et al., 2006). The techniques of Delphi are rooted in the social representation more than in statistics representation. This social representation is based on views of experts in the field of the research and investigation (Saizarbitoria Iñaki et al., 2006). The key factors to this type of research are the selection of the members of the panel which should be based on their knowledge, capabilities, and independence (Saizarbitoria Iñaki et al., 2006). It is highly recommended that the panel should include at least seven members and at most thirty members (Saizarbitoria Iñaki et al., 2006). Studies show that when the panel has a large group of experts, many of them do not demonstrate sufficient knowledge or capabilities, and accordingly, they withdraw from the panel prematurely increases (Saizarbitoria Iñaki et al., 2006). To minimize such premature withdrawal from the panel, it is critical that the experts must be selected carefully and receive the information about the objective of the study (Saizarbitoria Iñaki et al., 2006). The selected experts should be notified of the estimated time required for their participation, and the potential of the research and possible benefits they can obtain by participating in such a study (Saizarbitoria Iñaki et al., 2006). Delphi method minimizes the danger of dominant influence of any of the panel members by not identifying the members when expressing their opinions (Saizarbitoria Iñaki et al., 2006). Another success factor for Delphi method is rooted in the writing of the questions to be included in the different questionnaires (Saizarbitoria Iñaki et al., 2006).

The “Plop” method as a group decision-making technique works by providing different ideas about a subject and arguing them until the group reaches consensus on one of them (Ozcan et al., 2013; Schwartz, 1994). It is described to be simple and commonly used technique (Ozcan et al., 2013). However, it is not regarded to be appropriate for all types of group decisions (Ozcan et al., 2013). In (Ozcan et al., 2013), the “Plop” method is described similar to (Ozcan et al., 2013). However, (Schwartz, 1994) elaborated on the technique indicating that a member from the group proposes an idea before anyone else in the group, followed by another member proposes another idea until the group eventually finds one and agree upon it to act on (Schwartz, 1994). The result in shooting down the original idea before it is considered and the rejection of all other ideas, the members who proposed these rejected ideas feel their proposals have “plopped” (Schwartz, 1994). The member feels ignored and possibly rejected (Lauby, 2015). In (Rebori, NA) the “Plop” method is described as “no decision” technique where members avoid making decision consciously or unconsciously and thus make the decision not to decide (Rebori, NA). In this techniques member jumping from one topic to another, allowing the member to shift the topic before a decision is reached and by the “plop” (Rebori, NA). The plop is a board decision by “omission” (Rebori, NA). Thus, it is a decision not to decide (Rebori, NA). While the “Plop” method is common, it is the least visible technique for group decision making (Ozcan et al., 2013). The “Plop” method can be very useful when a person just refuses to believe the idea has any merit (Lauby, 2015).

References

Lauby, S. (2015). Essential Meeting Blueprints for Managers: Packt Publishing.

Minnesota, U. O. (2007). Typical Methods of Group Decision Making. Retrieve from http://www.minneapolismn.gov/www/groups/public/@ncr/documents/webcontent/convert_274389.pdf.

Ozcan, E., Misir, M., & Kheiri, A. (2013). Group decision making hyper-heuristics for function optimisation. Paper presented at the Computational Intelligence (UKCI), 2013 13th UK Workshop on.

Rebori, M. K. (NA). Community Board Development: Series 5. University of Nevada, Retrieved from https://www.unce.unr.edu/publications/files/cd/other/fs9856.pdf.

Ritchie, J., Lewis, J., Nicholls, C. M., & Ormston, R. (2013). Qualitative research practice: A guide for social science students and researchers: Sage.

Saizarbitoria Iñaki, H., Arana Landín, G., & Casadesús Fa, M. (2006). A Delphi study on motivation for ISO 9000 and EFQM. International Journal of Quality & Reliability Management, 23(7), 807-827.

Sarkissian, A. (2002). Different Techniques in Group Decision-Making. Retrieve from https://yourbusiness.azcentral.com/different-techniques-group-decisionmaking-17366.html.

Schwartz, A. E. (1994). Group decision-making. The CPA Journal, 64(8), 60.

Think Tank Methods

Dr. Aly, O.
Computer Science

Purpose

The purpose of this discussion is to discuss a technology and a key trend from this Web site: https://www.nmc.org/nmc-horizon/. The discussion will analyze at least two forces that impact the trend and the technology.

Note: For additional information on the sociotechnical process, review this Web site: http://horizon.wiki.nmc.org/

Discussion

This discussion is about “Think Tank.” Let us begin with the definition of “Think Tank” before we get to the NMC. The term “Think Tank” is defined as a structure for a group that focuses on providing a solution to a particular problem in the technology and science domain (Caliva & Scheier, 1992). However, it is regarded as a process rather than a structure by (Caliva & Scheier, 1992). Thus, the term can be defined as “a process for in-depth consideration of issues and challenges whose relevance reaches beyond the individual or program and the immediate time frame.” (Caliva & Scheier, 1992). In (Shaw, Russell, Greenhalgh, & Korica, 2014), Think Thank is described as “a civil society organization specializing in the production and dissemination of knowledge related to public policy” (Shaw et al., 2014). In (Whittenhauer, NA), the Think Tank is described as “an organization that assembles experts with the sole purpose of coming together to think—more specifically, to think of ideas on how to solve a particular problem” (Whittenhauer, NA). Most of the Think Tanks in the United States are funded by the government or political advocacy groups (Whittenhauer, NA). However, some of the Think Tank are established as for-profit organizations which sell their intellectual property or ideas to businesses and government (Whittenhauer, NA). There are two models for the Think Tank; the “one roof” Think Tank model and “without a roof” Think Tank model (Whittenhauer, NA). The “without a roof” Think Tank model is more effective than the “one roof” because it does not require the funding that is required by the “one roof” on travel costs and so forth. The “without roof” Think Tank model spends most of the money on research and the required costs for computers and utilities are not paid by think tank organization using this model (Whittenhauer, NA).

NMC Horizon Report 2017 Higher Ed Edition: This is a collaborative effort between NMC and the EduCause Learning Initiative (ELI) (NMC, 2018). This Edition is the fourteenth edition to describe the annual findings from the NMC Horizon Project. The purpose of this project is to identify and describe emerging technologies likely to have an impact on learning, teaching, and creative inquiry in education. The key trends for accelerating technology adoption in Higher Education include three modes of trends: long-term, mid-term and short-term (NMC, 2018). The main objective of the long-term trends is to drive ED Tech adoption in higher education for five or more year. The advancing cultures of innovation and deeper learning approaches are the two forces that are required to achieve the long-term trends (NMC, 2018). The main objective of the mid-term trends is to drive Ed Tech adoption in higher education for the next three to five years (NMC, 2018). The growing focus on measuring learning and redesigning learning spaces are the two forces that are required to achieve the mid-term trends (NMC, 2018). The main objective of the short-term trends is to drive Ed Tech adoption in higher education for the next one to two years. Two forces are required to achieve short-term trends which are the blended learning designs, and collaborative learning (NMC, 2018).

For the long-term trends, the advancing cultures of innovation force include many areas of higher education that are spreading innovation, including the advancing cultures of entrepreneurial thinking and designing new forms of artificial intelligence (AI) (NMC, 2018). It is considered to be the vehicle for driving the innovation. The focus of this trend has moved from understanding the value of fostering the exploration of new ideas to finding ways to replicate it across a span of diverse and unique learning institutions (NMC, 2018). The main element to enhance this force is to encourage higher education to modify its status quo to accept failure as an important part of the learning process. The integration of the entrepreneurship in the higher education is an important step in realizing that big ideas usually begin from somewhere (NMC, 2018). Students and faculties should be equipped with tools that are required to spark the real progress in that domain. Thus, the institution must evaluates and examine the curriculum and implement the required changes to remove any barriers that limit the development of new ideas (NMC, 2018). There is a need for policies that can assist institutions to better finance revolutionary practices encouraging the nations to be more strategic in the allocation of funds to invest in efforts that enhance the completion of programs and the attainment of degree (NMC, 2018).

The deeper learning approach force is defined by William and Flora Hewlett Foundation as “the mastery of content that engages students in critical thinking, problem-solving, collaboration, and self-directed learning” (NMC, 2018). The connection between the coursework and the real world is required to help student remain motivated. The deeper learning has proved that it is effective for improving the rates of the graduation in schools (NMC, 2018). The trend of the deeper learning approach force has been growing and is continuing to new developments. The active learning approach has two strategies of inquiry-based learning; the problem-based learning where students solve real challenges and project-based learning where they create completed products (NMC, 2018). There are no explicit policies that mandate project-based learning or other deeper learning approached in the universities or colleges. However, there is an effort from entities such as the Knowledge Alliances in Europe which represent projects intending to bring together post-secondary institutions and businesses to solve common problems (NMC, 2018). The emphasis is on to develop innovation using multi-disciplinary approaches to education, and simulating entrepreneurial skills in higher education; and exchanging knowledge (NMC, 2018). In the US, there are efforts from entities such as the Improving Career and Technical Education for the 21^st Century Act is to assist Americans to receive the skills that are required to compete for in-demand jobs. The purpose of these efforts is to support students to get involved in work-based learning opportunities and promote the use of new types of credentialing (NMC, 2018).

References

Caliva, L., & Scheier, I. H. (1992). The Think Tank Techniques. Retrieved from http://academic.regis.edu/volunteer/ivan/sect03/sect03b.htm.

NMC, H. P. (2018). NMC Horizon Report: 2017 Higher Education Edition. Retrieve from https://www.nmc.org/publication/nmc-horizon-report-2017-higher-education-edition/.

Shaw, S., Russell, J., Greenhalgh, T., & Korica, M. (2014). Thinking about Think Tanks in Health Care: a call for a New Research Agenda.

Whittenhauer, K. (NA). Effective Think Tank Methods. Retrieved from http://classroom.synonym.com/effective-think-tank-methods-5728092.html.

Proactive Model

Dr. Aly, O.
Computer Science

The purpose of this blog is to have a brainstorming blogging session about the “Proactive Model.” The computational intelligence and the machine learning techniques have gained popularity in different domains. Internet of things and internet of people are terms which can indicate the increasing interaction between humans and machines. Internet of Things (IoT) is regarded to be “one of the most promising fuels of Big Data expansion” (De Mauro, Greco, & Grimaldi, 2015). Internet of things is the core component of Web 4.0. The Web has gone from the first generation of Web 1.0 which was about static web pages, broadcasting information for read-only. Web 1.0 was innovated by Berners-Lee (Aghaei, Nematbakhsh, & Farsani, 2012; Choudhury, 2014; Kambil, 2008; Patel, 2013), and is known as the “Web of Information Connections” (Aghaei et al., 2012). Web 2.0 which came out in 2004 is read-write and is known as the “Web of People Connections (Aghaei et al., 2012) to connect people. Web 3.0 which came out in 2006 is known as “Semantic Web” or the “Web of Knowledge Connections” to share knowledge, followed by Web 4.0 is known as the “Web of Intelligence Connections” where Artificial Intelligence (AI) is expected to play a role. The current technology as indicated in TED’s video of (Hougland, 2014) can assist people to save lives in case of unexpected health issues such as the heart attack or stroke, by wearing a band in hand. There are also other tools for elder people to save them when they fall, and they need help while living alone by themselves with no assistance. These tools are reactive tools which can assist after the fact. The question is:

“Can the “Web of Intelligence Connections” be intelligent enough to be proactive and provide us with useful information on a daily basis?”

As a computer science researcher, who started with Web 1.0 and experienced the amazing evolution of the Web, I believe that our children will have better opportunities and better health because of the “Proactive Model.” They will have far advanced tools through which they will communicate daily about what to eat, when to exercise, what to drink, and basically what to do. For instance, the tool that is based on the “Proactive Model” will monitor the glucose level, the cholesterol level, the potassium level and so forth daily to be able to intelligently tell you what is lacking in your body and what you need to do to fill that gap. If the person has low potassium, the tool can suggest eating some food such as banana to fill that gap of the potassium level. If the person has high cholesterol level, the tool can intelligently inform the person of such a fact that can cause damage at heart and provide recommendations to overcome such high cholesterol before it gets worse and lead to the heart attack. This “Proactive Model” will get embedded into our future children lives and be part of their lives.

The healthcare system may raise the question about their role in that model, and the impact of this model on the practice of the doctors. The health care system should drive this model. The doctors will play a role in these tools as the recommendations will be based on medical practices. These recommendations are not arbitrarily and must be based on the recommendation of the doctors the same way when you go to visit the doctor. On the other hand, the practice of the doctors will be more focused on more serious things that cannot be proactively controlled such as car accidents, or any unexpected or anticipated accidents.

Do you think it is possible to have such intelligent and sophisticated “Proactive Model?” If so, how do you vision the model and what obstacles do you think it will face?

References

Aghaei, S., Nematbakhsh, M. A., & Farsani, H. K. (2012). Evolution of the world wide web: From WEB 1.0 TO WEB 4.0. International Journal of Web & Semantic Technology, 3(1), 1.

Choudhury, N. (2014). World Wide Web and its journey from web 1.0 to web 4.0.

De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. Paper presented at the AIP Conference Proceedings.

Hougland, B. (2014). What is the Internet of Things? And why should you care? [Video file]. TED Talks: Retrieved from https://www.youtube.com/watch?v=_AlcRoqS65E.

Kambil, A. (2008). What is your Web 5.0 strategy? Journal of business strategy, 29(6), 56-58.

Patel, K. (2013). The incremental journey for World Wide Web: introduced with Web 1.0 to recent Web 5.0–a survey paper.

The Futurists

Dr. Aly, O.
Computer Science

Purpose

The purpose of this discussion is to visit this Web site, review various videos, and find one that addresses an innovation that you find interesting. We will introduce and discuss the content of a video, addressing the innovation from this Website, and post a reference for the video. We will also analyze two forces that impact the innovation being discussed in the video.

Discussion

As indicated in (Petranek, 2015), there is a notion that our kids can live on Mars. Although this idea might sound unreasonable and “preposterous,” however, there are reasons for considering Mars as our habitable planet after Earth. These reasons include our vulnerability in our home Earth and the fact that we as humans like to explore.

When John Kennedy announced the possibility of sending a human to the moon, this news was so exciting. Landing on Mars is so inspiring as well. The notion of living on Mars can inspire the unity concept by identifying us as the people of Earth. If we struggle on Mars, we can appreciate our Earth home more than we do now.

Behind every innovative notion, there must be various questions to find out the opportunities and the challenges. Some of these questions are:

Is it possible to live on Mars?
What forces will impact the implementation of such exciting notion to live on Mars?
How is Mars different from our home Earth?

Mars and Earth are two different planets, and they are not considered as siblings. Regarding size, The Earth is bigger than Mars; Mars is less than half of the Earth. The surface area of the Earth is almost the same as on Mars. The Earth is mostly covered by water. The atmosphere on Earth 100 time thicker than on Mars, and you cannot breathe through the thin atmosphere of Mars. Moreover, Mars has 96% carbon dioxide and is cold with an average of -81 degrees. The day on Mars is 24 hours and 39 minutes long. Mars has less gravity than Earth. The years and seasons on Mars are twice as long as on Earth. Although Mars is different from the Earth, it is the most livable planet in our solar system after the Earth.

The distance between the Earth and Mars is 250 million miles, and it takes eight months to travel to Mars if the Earth and Mars are aligned to have the shortest way. Our attempts to Mars have not been successful all the time. Forty-four rockets were sent, and only third of them was successful. The rocket used for landing on Moon was Saturn V. However, Saturn V is no longer in existence, and it was replaced by a shuttle. The current rocket is not big enough to send anything to Mar.

There is a prediction from NASA that we will travel to Mars by 2040. However, Elon Musk the CEO of Tesla Motors and SpaceX is determined to get us to Mars by 2025. Elon Musk is regarded to be optimistic. Thus we can give him up to 2027. Elon Musk accomplished electric cars in less than ten years, and created the rocket company in less than ten years, and is expected to get us to Mars sooner than 2040; probably by 2025 or 2027.

Some forces will affect the implementation of living on Mars. These forces are Water, Oxygen, Food, Shelter, and Clothing. For the water, the soil in Mars was found to contain sixty percent water, and a huge amount of underground water was found on Mars. Moreover, the atmosphere of Marsh is often 100% humid, which can be extracted to serve as water. The University of Washington developed a low-tech dehumidifier in 1998, which can assist in such extraction.

For the Oxygen, Michael Hecht a scientist at MIT developed a machine that reverses fuel cell by sucking in the Martian atmosphere and pumps out oxygen. The atmosphere of Mars has 96% carbon dioxide (CO2) which contains 78% oxygen.

For the food, until the water is running on Mars, we will be able to plant only 15-20 percent of the food, and the rest of the supplies will come from earth dried. For the shelter, we will have to go underground due to the radiation from the cosmic. For the clothing, Dava Newman a scientist at MIT has developed sleek space suit, which will block radiation and keep us warm.

The key elements are covered, and the notion of living on Mars seems possible. So, Mars will be re-engineered to be like Earth and be habitable. The oxygen challenge is expected to take a thousand year to accomplish. However, we get adapted quickly. We might end with two different species, one on Earth and another adapted one on Mars.

In conclusion, we cannot imagine where our technology will take us and how far we can go. What seemed to be impossible ten years ago, it is now possible and disappeared as it is embedded in our lives. Innovation begins with a vision that is driven by a passion for changing the world, or by being proactive to solve a problem that is ignored by most people.

References

Petranek, S. (2015). Your Kids might live on Mars. Here is how they will survive [Video file]. TED Talks: Retrieved from https://www.ted.com/talks/stephen_petranek_your_kids_might_live_on_mars_here_s_how_they_ll_survive/transcript.