New Technologies of the Fourth Industrial Revolution: AI, IoT, Robotics, and Beyond
New Technologies of the Fourth Industrial
Revolution: AI, IoT, Robotics, and Beyond
CTO & Professor, University of Rhode Island Libraries
Before we begin,
This talk is based upon my book, Moving Forward with Digital
Disruption (ALA TechSource, 2020).
You can download the full book at :
I. What is the Fourth Industrial Revolution (4IR)?
II. Some of the main technologies of the 4IR
III. Disruption and transformation of the entire systems of production, management, and governance
IV. Opportunities and challenges for libraries
The Second Machine Age
• Began at the turn of the twenty-first century.
• Machines are starting to perform not only physical and
mechanical but also cognitive tasks.
• With the recent breakthroughs in machine learning,
automation is spreading to areas that used to be seen as the
exclusive domain of humans, such as translation, driving,
object identification, and news writing.
• The 3rd industrial revolution: digital (1960s-1990s)
• The first industrial revolution mechanized production,
using water and steam power;
• The second industrial revolution created mass
production with electricity and the assembly line;
• The third industrial revolution automated production with
electronics and information technology.
The Fourth Industrial Revolution
• Began at the turn of the twenty-first century.
• Characterized by:
• A much more ubiquitous and mobile internet;
• Smaller, more powerful, and cheaper sensors;
• And the use of Big Data with AI, particularly machine learning/deep learning.
• What differentiates the fourth industrial revolution is the fusion of these technologies and their
interaction across the physical, digital, and biological domains.
• A qualitatively distinct stage of digital revolution
• Blurring the lines between the physical, digital, and biological spheres.
• Disrupting and transforming entire systems of production, governance, and management (/employment).
II.The Blurring of the Physical, the
Digital, and the Biological
Technologies of the 4IR
• XR (Extended Reality)
• Big Data (/Machine Learning & Deep Learning) & IoT (Internet of Things)
• Synthetic biology and 3D bio-printing
• 3 Vs of Big Data: high-volume, high-velocity, and high-variety
• Big Data also refers to the technologies that support storing, organizing, searching, retrieving,
and analyzing the huge amount of digital data.
Infographic: https://www.domo.com/learn/data-never-sleeps-8; Watson Marketing,
10 Key Marketing Trends for 2017 and Ideas for Exceeding Customer
Expectations, white paper (IBM, 2017), accessed October 17, 2019,
wrl12345usen-20170719.pdf; Knud Lasse Lueth, “State of the IoT 2018: Number
of IoT Devices Now at 7B—Market Accelerating,” IOT Analytics (blog), August 8,
devices-now-7b ; “The Growth in Connected IoT Devices Is Expected to Generate
79.4ZB of Data in 2025, According to a New IDC Forecast,” International Data
Corporation, June 18, 2019,
• The Internet of Things (IoT) is an
important contributor to Big Data
because it generates a large volume of
• More than 17 billion connected devices
currently in use worldwide, including 7
billion IoT devices.
• IDC estimates that there will be 41.6
billion IoT devices in 2025, generating
79.4 zettabytes (= 79.4 billion TB) of
IoT (Internet ofThings)
• The IoT is the network of uniquely identifiable things—that is, physical objects digitally
represented on the Internet (through sensors and actuators).
• The network of those sensors and systems captures, reports, and communicates data about their
environments as well as their own performances and interacts with their environments.
• A smartwatch, a smart thermostat, a Fitbit, and an Amazon Alexa are all examples of IoT devices.
Big Data – ML/DL - IoT
• What makes Big Data different from just more data is its ability to apply sophisticated algorithms
and powerful computers to large data sets, in order to reveal correlations and insights, which
were previously inaccessible through conventional data warehousing or business intelligence
• This is where machine learning comes in.
• The more physical objects are brought into the IoT network, the more digital data they will
generate. And this massive amount of data will fuel the developments of more accurate machine
Physical = Digital
• Just like XR, the IoT aims to create a digital layer over our physical world, thereby blurring the line
between the physical and the digital realm.
• And in the mature stages of the XR and the IoT, things in the world will be digital as much as
Synthetic Biology & 3D Bio-printing
• They are transforming biological processes into digital ones with genetic circuits and biological
• What does that mean?
TheVision of SynBio
• To re-purpose living cells as substrates for general computation.
• That vision has so far manifested itself in genetic circuit designs that attempt to implement
Boolean logic gates, digital memory, oscillators, and other circuits from electrical engineering.
• Biological circuits and parts are not yet sufficiently modular or scalable.
• But synthetic biology holds a key to the potential future in which electronics and biology become
fungible and matter becomes programmable.
Biological = Digital = Physical
• When this happens, the function of a mechanical sensor, for example, may be performed by
bacteria, and those bacteria may function in connection with electronics and computers.
• In such a future, living organisms and non-organic matter will interface and interact with each
• One day, we may well use living organisms to produce materials, and living organisms may serve
as an interface for everyday electronics.
• When developments in the areas of computational design, additive manufacturing, materials
engineering, and synthetic biology are combined, it will truly result in the merging of the physical,
the digital, and the biological sphere into one reality.
Online Platform Business
• A platform business enables value-creating interactions between external producers and consumers. It
provides an infrastructure for those interactions and sets governance conditions for them in order to
find matches among users and facilitate the exchange of goods, services, and social currency.
• Almost all successful traditional businesses own and maintain large physical infrastructure and assets
to process raw materials. They produce goods or services and hire employees. But today’s platform
businesses do not produce goods or services.
• They also tend to own fewer means of production if not none. Rather, they create and maintain the
means of connection.
• Platform businesses produce connections at an unprecedentedly large scale with the help of digital
• This is the kind of change that digital disruption is bringing to the area of production.
A. Production - AI/ ML /DL
• But digital technologies can certainly be used to produce goods and services too.
• Artificial intelligence (AI) is the technology behind the new phenomenon of machine-generated
content and services.
B. Governance - Blockchain
• Governance refers to establishing, monitoring, and implementing the rules and procedures for an
organization to properly function.
• Digital technologies excel at connecting a large number of people on the Web and facilitating
activities or transactions. This creates the potential to decentralize the governance role of a third-
party authority or even eliminate it altogether.
• Blockchain is the technology that is in the center of this new possibility.
• Blockchain refers to the distributed ledger technology
• Traditionally, a third-party authority is brought into important transactions, such as fund transfer,
real estate purchase and sales, insurance, and any type of credentialing, from school graduation
to marriage certification.
• The role of a third-party authority in those cases is to guarantee the authenticity of the transaction
and the integrity of the recordation process.
• However, without relying on any outside party with existing authority, blockchain can serve as a
trust protocol that enables transactions on the Web to be validated, authorized, and recorded in a
secure manner using the distributed network and the hashing process only.
C. Management – Sharing Economy
• Platform businesses of the so-called sharing economy such as Uber, enable direct peer-to-peer
(P2P) market transactions with technology.
• These P2P transaction platform businesses introduced much disruption to the established roles of
an employer and an employee.
• In the traditional economic model, businesses hire employees and pay them wages. Managing
and supervising these workers is the responsibility of an employer. Employees are entitled to fair
labor practices from their employers, while being supervised for work performance. Employers are
also to provide a level of support and direction for employees when disputes arise in their
interactions with customers.
Contingent Labor for Platform Businesses
• Platform companies practically broke all of these well-established conventions in the employer-
• For example, Uber does not regard its drivers as employees and itself as their employer. Instead, it calls
Uber drivers “Uber entrepreneurs.”
• It also argues that Uber drivers are the users (or consumers) of its platform just like Uber passengers.
• Online platform companies prefer to conflate workers and customers as the same “users or
consumers” of platform services and “members” of their so-called “community.”
• But we know that the role of those who work on a platform such as Uber is not so different from that of
traditional workers. Just like traditional workers, Uber drivers make a living by working for Uber, and
their work is essential to Uber’s revenue generation.
• To stay relevant to the evolving needs of library users, libraries must continue to invest in
technology-related offerings and innovate library services and programs.
• This is not something that is opposite to or competes with what some consider to be more
traditional types of library services and programs.
• This is because technology is to help the library achieve its mission, not to change it.
• No matter what technology the library adopts and no matter how it changes the library’s services,
programs, and other offerings, the library’s mission —to empower people through knowledge and
to facilitate and support their information-seeking and learning activities— does not change.
Libraries' Commitment to Social Good
• Technology does not always produce social good; it can bring negative social consequences.
• Libraries are institutions that aim to generate and increase social good in the communities that
• Therefore, library professionals must be attuned not only to the benefits but also to the limitations
of new technologies adopted by a society.
• Blind optimism about technology;
• Lack of caution about how new technologies will be used;
• Disregard for social convention for the sake of building new things;
• Prioritization of efficient code above human interactions;
• Worship of the cult of genius that camouflages a range of structural discrimination;
• Techno-libertarianism and counter-culture for radical individuality; and
• Inability to reconcile the demands of being an individual with the demands of participating in a
society, as if they were incompatible with each other.
Broussard, Meredith. Artificial Unintelligence: How Computers Misunderstand the World. Cambridge, Massachusetts: The MIT
Navigating through Radical Changes
• Libraries can consciously try to adopt and utilize technology in ways that create and contribute to
• Technology can serve as an equalizer and democratizer for our society.
• Technology can also equally well function as a divider and an amplifier of existing discrimination.
• Technology is not inherently liberating. Nor does it solve every problem and automatically bring
• By remembering this, I believe that libraries will be well served in navigating the new and
unprecedented changes brought on by the fourth industrial revolution.
This talk is based upon my book, Moving Forward with Digital
Disruption (ALA Techsource, 2020).
• Download at https://journals.ala.org/index.php/ltr/issue/view/752
Bohyun Kim / @bohyunkim (Twitter)