by Klaus Schwab
Shift 8: The Internet of and for Things
The tipping point: 1 trillion sensors connected to the internet
By 2025: 89% of respondents expected this tipping point to have occurred
With continuously increasing computing power and falling hardware prices (still in line with Moore’s Law90), it is economically feasible to connect literally anything to the internet. Intelligent sensors are already available at very competitive prices. All things will be smart and connected to the internet, enabling greater communication and new data-driven services based on increased analytics capabilities.
A recent study looked into how sensors can be used to monitor animal health and behaviour.91 It demonstrates how sensors wired in cattle can communicate to each other through a mobile phone network, and can provide real-time data on cattle conditions from anywhere.
Experts suggest that, in the future, every (physical) product could be connected to ubiquitous communication infrastructure, and sensors everywhere will allow people to fully perceive their environment.
Positive impacts
– Increased efficiency in using resources
– Rise in productivity
– Improved quality of life
– Effect on the environment
– Lower cost of delivering services
– More transparency around the use and state of resources
– Safety (e.g. planes, food)
– Efficiency (logistics)
– More demand for storage and bandwidth
– Shift in labour markets and skills
– Creation of new businesses
– Even hard, real-time applications feasible in standard communication networks
– Design of products to be “digitally connectable”
– Addition of digital services on top of products
– Digital twin provides precise data for monitoring, controlling and predicting
– Digital twin becomes active participant in business, information and social processes
– Things will be enabled to perceive their environment comprehensively, and react and act autonomously
– Generation of additional knowledge, and value based on connected “smart” things
Negative impacts
– Privacy
– Job losses for unskilled labour
– Hacking, security threat (e.g. utility grid)
– More complexity and loss of control
Unknown, or cuts both ways
– Shift in business model: asset rental/usage, not ownership (appliances as a service)
– Business model impacted by the value of the data
– Every company potentially a software company
– New businesses: selling data
– Change in frameworks to think about privacy
– Massively distributed infrastructure for information technologies
– Automation of knowledge work (e.g. analyses, assessments, diagnoses)
– Consequences of a potential “digital Pearl Harbor” (i.e. digital hackers or terrorists paralysing infrastructure, leading to no food, fuel and power for weeks)
– Higher utilization rates (e.g. cars, machines, tools, equipment, infrastructure)
The shift in action
The Ford GT has 10 million lines of computer code in it.
Source: http://rewrite.ca.com/us/articles/security/iot-is-bringing-lots-of-code-to-your-car-hackers-too.html?intcmp=searchresultclick&resultnum=2).
The new model of the popular VW Golf has 54 computer processing units; as many as 700 data points get processed in the vehicle, generating six gigabytes of data per car.
Source: “IT-Enabled Products and Services and IoT”, Roundtable on Digital Strategies Overview, Center for Digital Strategies at the Tuck School of Business at Dartmouth, 2014
More than 50 billion devices are expected to be connected to the internet by 2020. Even the Milky Way, the earth’s galaxy, contains only around 200 billion suns!
Eaton Corporation builds sensors into certain high-pressure hoses that sense when the hose is about to fray, preventing potentially dangerous accidents and saving the high costs of downtime of the machines that have the hoses as a key component.
Source: “The Internet of Things: The Opportunities and Challenges of Interconnectedness”, Roundtable on Digital Strategies Overview, Center for Digital Strategies at the Tuck School of Business at Dartmouth, 2014
Already last year, according to BMW 8% of cars worldwide, or 84 million, were connected to the internet in some way., That number will grow to 22%, or 290 million cars, by 2020.
Source: http://www.politico.eu/article/google-vs-german-car-engineer-industry-american-competition/
Insurance companies like Aetna are thinking about how sensors in a carpet could help if you’ve had a stroke. They would detect any gait change and have a physical therapist visit.
Source: “The Internet of Things: The Opportunities and Challenges of Interconnectedness”, Roundtable on Digital Strategies Overview, Center for Digital Strategies at the Tuck School of Business at Dartmouth, 2014
Shift 9: The Connected Home
Tipping point: Over 50% of internet traffic delivered to homes for appliances and devices (not for entertainment or communication)
By 2025: 70% of respondents expected this tipping point to have occurred
In the 20th century, most of the energy going into a home was for direct personal consumption (lighting). But over time, the amount of energy used for this and other needs was eclipsed by much more complex devices, from toasters and dishwashers to televisions and air conditioners.
The internet is going the same way: most internet traffic to homes is currently for personal consumption, in communication or entertainment. Moreover, very fast changes are already occurring in home automation, enabling people to control lights, shades, ventilation, air conditioning, audio and video, security systems and home appliances. Additional support is provided by connected robots for all kinds of services – as, for example, vacuum cleaning.
Positive impacts
– Resource efficiency (lower energy use and cost)
– Comfort
– Safety/security, and detection of intrusions
– Access control
– Home sharing
– Ability to live independently (young/old, those disabled)
– Increased targeted advertising and overall impact on business
– Reduced costs of healthcare systems (fewer hospital stays and physician visits for patients, monitoring the drug-taking process)
– Monitoring (in real-time) and video recording
– Warning, alarming and emergency requests
– Remote home control (e.g. close the gas valve)
Negative impacts
– Privacy
– Surveillance
– Cyber attacks, crime, vulnerability
Unknown, or cuts both ways
– Impact on workforce
– Change in work’s location (more from and outside the home)
– Privacy, data ownership
The shift in action
An example of this development for use in the home was cited by cnet.com:
“Nest, makers of the Internet-connected thermostat and smoke detector … announced [in 2014] the ‘Works with Nest’ developer program, which makes sure products from different companies work with its software. For example, a partnership with Mercedes Benz means your car can tell Nest to turn up the heat at home so it’s warm when you arrive … Eventually … hubs like Nest’s will help the home sense what you need, adjusting everything automatically. The devices themselves might eventually disappear into the home, merely acting as sensors and devices controlled from a single hub.”
Source: “Rosie or Jarvis: The future of the smart home is still in the air”, Richard Nieva, 14 January 2015, http://www.cnet.com/news/rosie-or-jarvis-the-future-of-the-smart-home-is-still-in-the-air/
Shift 10: Smart Cities
Tipping point: The first city with more than 50,000 inhabitants and no traffic lights
By 2025: 64% of respondents expected this tipping point to have occurred
Many cities will connect services, utilities and roads to the internet. These smart cities will manage their energy, material flows, logistics and traffic. Progressive cities, such as Singapore and Barcelona, are already implementing many new data-driven services, including intelligent parking solutions, smart trash collection and intelligent lighting. Smart cities are continuously extending their network of sensor technology and working on their data platforms, which will be the core for connecting the different technology projects and adding future services based on data analytics and predictive modelling.
Positive impacts
– Increased efficiency in using resources
– Rise in productivity
– Increased density
– Improved quality of life
– Effect on the environment
– Increased access to resources for the general population
– Lower cost of delivering services
– More transparency around the use and state of resources
– Decreased crime
– Increased mobility
– Decentralized, climate friendly energy production and consumption
– Decentralized production of goods
– Increased resilience (to impacts of climate change)
– Reduced pollution (air, noise)
– Increased access to education
– Quicker/speed up accessibility to markets
– More employment
– Smarter e-government
Negative impacts
– Surveillance, privacy
– Risk of collapse (total black out) if the energy system fails
– Increased vulnerability to cyber attacks
Unknown, or cuts both ways
– Impact on city culture and feel
– Change of individual habitus of cities
The shift in action
According to a paper published in The Future Internet:
“The city of Santander in northern Spain has 20,000 sensors connecting buildings, infrastructure, transport, networks and utilities. The city offers a physical space for experimentation and validation of functions, such as interaction and management protocols, device technologies, and support services such as discovery, identity management and security”.
Source: “Smart Cities and the Future Internet: Towards Cooperation Frameworks for Open Innovation”, H. Schaffers, N. Komninos, M. Pallot, B. Trousse, M. Nilsson and A. Oliveira, The Future Internet, J. Domingue et al. (eds), LNCS 6656, 2011, pp. 431-446, http://link.springer.com/chapter/10.1007%2F978-3-642-20898-0_31
Shift 11: Big Data for Decisions
The tipping point: The first government to replace its census with big-data sources
By 2025: 83% of respondents expected this tipping point to have occurred
More data exists about communities than ever before. And, the ability to understand and manage this data is improving all the time. Governments may start to find that their previous ways of collecting data are no longer needed, and may turn to big-data technologies to automate their current programmes and deliver new and innovative ways to service citizens and customers.
Leveraging big data will enable better and faster decision-making in a wide range of industries and applications. Automated decision-making can reduce complexities for citizens and enable businesses and governments to provide real-time services and support for everything from customer interactions to automated tax filings and payments.
The risks and opportunities in leveraging big data for decision-making are significant. Establishing trust in the data and algorithms used to make decisions will be vital. Citizen concerns over privacy and establishing accountability in business and legal structures will require adjustments in thinking, as well as clear guidelines for use in preventing profiling and unanticipated consequences. Leveraging big data to replace processes that today are done manually may render certain jobs obsolete, but may also create new categories of jobs and opportunities that currently do not exist in the market.
Positive impacts
– Better and faster decisions
– More real-time decision-making
– Open data for innovation
– Jobs for lawyers
– Reduced complexity and more efficiency for citizens
– Cost savings
– New job categories
Negative impacts
– Job losses
– Privacy concerns
– Accountability (who owns the algorithm?)
– Trust (how to trust data?)
– Battles over algorithms
Unknown, or cuts both ways
– Profiling
– Change in regulatory, business and legal structures
The shift in action
The volume of business data worldwide, across all companies, doubles every 1.2 years.
Source: “A Comprehensive List of Big Data Statistics,” Vincent Granville, 21 October 2014: http://www.bigdatanews.com/profiles/blogs/a-comprehensive-list-of-big-data-statistics
“Farmers from Iowa to India are using data from seeds, satellites, sensors, and tractors to make better decisions about what to grow, when to plant, how to track food freshness from farm to fork, and how to adapt to changing climates.”
Source: “What’s the Big Deal with Data”, BSA | Software Alliance, http://data.bsa.org/
“To better inform restaurant-goers about unsanitary venues, San Francisco successfully piloted a collaboration with Yelp—fusing the city’s restaurant health inspection data onto the site’s restaurant review pages. If you open up the page of restaurant Tacos El Primo, for example, it shows a health score of 98 out of 100 (below). Yelp ratings are pretty powerful. Apart from serving as a mouthpiece for the city to tell residents about food hazards, the collaboration is potentially a way to shame repeat-offender restaurants into complying with health standards.”
Source: http://www.citylab.com/cityfixer/2015/04/3-cities-using-opendata-in-creative-ways-to-solve-problems/391035/
Shift 12: Driverless Cars
The tipping point: Driverless cars equalling 10% of all cars on US roads
By 2025: 79% of respondents expected this tipping point to have occurred
Trials of driverless cars from large companies such as Audi and Google are already taking place, with a number of other enterprises ramping up efforts to develop new solutions. These vehicles can potentially be more efficient and safer than cars with people behind the steering wheel. Moreover, they could reduce congestion and emissions, and upend existing models of transportation and logistics.
Positive impacts
– Improved safety
– More time for focusing on work and/or consuming media content
– Effect on the environment
– Less stress and road rage
– Improved mobility for those older and disabled, among others
– Adoption of electric vehicles
Negative impacts
– Job losses (taxi and truck drivers, car industry)
– Upending of insurance and roadside assistance (“pay more to drive yourself”)
– Decreased revenue from traffic infringements
– Less car ownership
– Legal structures for driving
– Lobbying against automation (people not allowed to drive on freeways)
– Hacking/cyber attacks
The shift in action
In October 2015, Tesla made its cars that were sold over the last year in the US semi-autonomous via a software update.
Source: http://www.wired.com/2015/10/tesla-self-driving-over-air-update-live
Google plans to make autonomous cars available to the public in 2020.
Source: Thomas Halleck, 14 January 2015, “Google Inc. Says Self-Driving Car Will Be Rea
dy By 2020”, International Business Times: http://www.ibtimes.com/google-inc-says-self-driving-car-will-be-ready-2020-1784150
In the summer of 2015, two hackers demonstrated their ability to hack into a moving car, controlling its dashboard functions, steering, brakes etc., all through the vehicle’s entertainment system.
Source: http://www.wired.com/2015/07/hackers-remotely-kill-jeep-highway/
The first state in the United States (Nevada) to pass a law allowing driverless (autonomous) cares did so in 2012.
Source: Alex Knapp, 22 June 2011, “Nevada Passes Law Authorizing Driverless Cars”, Forbes: http://www.forbes.com/sites/alexknapp/2011/06/22/nevada-passes-law-authorizing-driverless-cars/
Shift 13: Artificial Intelligence and Decision-Making
The tipping point: The first Artificial Intelligence (AI) machine on a corporate board of directors
By 2025: 45% of respondents expected this tipping point to have occurred
Beyond driving cars, AI can learn from previous situations to provide input and automate complex future decision processes, making it easier and faster to arrive at concrete conclusions based on data and past experiences.
Positive impacts
– Rational, data-driven decisions; less bias
– Removal of “irrational exuberance”
– Reorganization of outdated bureaucracies
– Job gains and innovation
– Energy independence
– Advances in medical science, disease eradication
Negative impacts
– Accountability (who is responsible, fiduciary rights, legal)
– Job losses
– Hacking/cybercrime
– Liability and accountability, governance
– Becoming incomprehensible
– Increased inequality
– “Falling foul of the algorithm”
– Existential threat to humanity
The shift in action
ConceptNet 4, a language AI, recently passed an IQ test better than most four-year-olds – three years ago it could barely compete with a one-year-old. The next version, just finalized, is expected to perform on level with a five- to six year-old.
Source: “Verbal IQ of a Four-Year Old Achieved by an AI System”: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.386.6705&rep=rep1&type=pdf