2021 Tech Trends Report - Artificial Intelligence
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Volume 1 of 12 14th Annual Edition 2021 Tech Trends Report Artificial Strategic trends that will influence business, Intelligence government, education, media and society in the coming year.
00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence
03 Overview 19 Algorithm Marketplaces 32 Machine Image Completion 43 Nation-based Guardrails
04 Macro Forces and Emerging Trends 19 100-Year Software 32 Predictive Models Using and Regulations
06 Summary 20 Scenario: Rage Against the Machine Single Images 43 Regulating Deepfakes
08 Artificial Intelligence 22 Health, Medicine, and Science 33 Model-free Approaches to RL 43 Making AI Explain Itself
09 An Executive’s Guide to AI 22 AI Speeds Scientific Discovery 33 Real-time Machine Learning 43 New Strategic Technical Alliances
09 Machine Learning 22 AI-First Drug Discovery 33 Automated Machine Learning 43 The New Mil-Tech
(AutoML) Industrial Complex
09 Deep Learning 23 AI Improves Patient Outcomes
33 Hybrid Human-Computer Vision 44 Algorithmic Warfighting
10 Weak and Strong AI 23 Deep Learning Applied to
Medical Imaging 33 Neuro-Symbolic AI
12 Enterprise
23 NLP Algorithms Detect Virus 33 General Reinforcement
12 The Rise of MLOps
Mutations Learning Algorithms
12 Low-Code or No-Code
23 Diagnostics Without Tests 34 Continuous Learning
Machine Learning 45 China’s AI Rules
23 Protein Folding 34 Proliferation of
12 Web-Scale Content Analysis 48 Society
Franken-Algorithms
12 Simulating Empathy and Emotion 23 Dream Communication
34 Proprietary, Homegrown 48 Ethics Clash
13 Artificial Emotional Intelligence 24 Thought Detection
AI Languages 48 Ambient Surveillance
13 Serverless Computing 25 Scenario: Deep Twins in the OR
36 Talent 48 Marketplace Consolidation
14 Expert Insight: Emotion AI Will 27 Consumer
36 AI Brain Drain 48 Fragmentation
Power the Empathy Economy, 27 Zero UIs
36 AI Universities 49 Expert Insight: AI reveals
but AI Still Needs to Work 27 Consumer-grade AI Applications
37 Demand for AI Talent Growing our real-world biases
17 AI in the Cloud 27 Ubiquitous Digital Assistants
37 Corporate AI Labs 50 AI Still Has a Bias Problem
17 AI at the Edge 28 Deepfakes for Fun
37 AI for Interviews 50 Problematic Training Data
17 Advanced AI Chipsets 28 Personal Digital Twins
39 Creative 50 AI to Catch Cheaters
17 Digital Twins 30 Research
39 Assisted Creativity 50 Algorithms Targeting
17 Spotting Fakes 30 Closed-Source Code Vulnerable Populations
39 Generative Algorithms for
18 Natural Language Processing 30 Framework Consolidation 51 AI Intentionally Hiding Data
Content Production
for ESGs
30 Cost of Training Models 39 Generating Virtual Environments 51 Undocumented AI Accidents
18 Intelligent Optical Character
31 NLP Benchmarks from Short Videos 51 Digital Dividends
Recognition
31 Machine Reading Comprehension 40 Automated Versioning 51 Prioritizing Trust
18 Robotic Process Automation
31 AI Summarizing Itself 40 Automatic Voice Cloning 52 Scenario: Bully Bots
18 Massive Translation Systems
31 No Retraining Required and Dubbing 53 Application
19 Predicting Systems and
31 Graph Neural Networks 40 Automatic Ambient Noise Dubbing 54 Key Questions
Site Failures
31 Federated Learning 42 Geopolitics and Defense 55 Sources
19 Liability Insurance for AI
31 GP Models 42 AI Nationalism 56 Authors
19 Manipulating AI Systems for
Competitive Advantage 31 GPT-3’s Influence 42 National AI Strategies
19 Global Rush to Fund AI 32 Vokenization 42 AI as Critical Infrastructure
00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence
Overview
The 1920s began in chaos. Cata- It’s difficult not to see striking ed trends. In total, we’ve analyzed
clysmic disruption resulting from parallels to our modern world. A nearly 500 technology and science
the first world war and the Spanish tumultuous U.S. election, extreme trends across multiple industry
flu shuttered businesses and pro- weather events and Covid-19 sectors. In each volume, we discuss
voked xenophobia. Technological continue to test our resolve and the disruptive forces, opportunities
marvels like the radio, refrigerator, our resilience. Exponential tech- and strategies that will drive your
vacuum cleaner, moving assembly nologies—artificial intelligence, organization in the near future.
line and electronic power trans- synthetic biology, exascale com-
Now, more than ever, your organi-
mission generated new growth, puting, autonomous robots, and
zation should examine the poten-
even as the wealth gap widened. off-planet missions to space—are
tial near and long-term impact of
More than two-thirds of Ameri- challenging our assumptions about
tech trends. You must factor the
cans survived on wages too low to human potential. Under lockdown,
trends in this report into your stra-
sustain everyday living. The pace we’ve learned how to work from
tegic thinking for the coming year,
of scientific innovation—the dis- our kitchen tables, lead from our
and adjust your planning, opera-
covery of insulin, the first modern spare rooms, and support each
tions and business models accord-
antibiotics, and insights into theo- other from afar. But this disruption
ingly. But we hope you will make
retical physics and the structure of has only just begun.
time for creative exploration. From
atoms—forced people to reconsid-
With the benefit of both hindsight chaos, a new world will come.
er their cherished beliefs.
and strategic foresight, we can
The sheer scale of change, and the choose a path of reinvention. Our
great uncertainty that came with 2021 Tech Trends Report is de-
it, produced two factions: those signed to help you confront deep
who wanted to reverse time and uncertainty, adapt and thrive. For Amy Webb
return the world to normal, and this year’s edition, the magnitude
Founder
those who embraced the chaos, of new signals required us to cre-
The Future Today Institute
faced forward, and got busy build- ate 12 separate volumes, and each
ing the future. report focuses on a cluster of relat-
03 © 2021 Future Today Institute
00 01 02 03 04 05 06 07 08 09 10 11 12
6
1
Macro Forces and
Emerging Trends 2 3 4 5
For nearly two decades, the Future Today Institute has meticulously re-
searched macro forces of change and the emerging trends that result.
Our focus: understanding how these forces and trends will shape our
futures. Our 14th annual Tech Trends Report identifies new opportunities
for growth and potential collaborations in and adjacent to your business.
We also highlight emerging or atypical threats across most industries,
including all levels of government. For those in creative fields, you will find
a wealth of new ideas that will spark your imagination.
Our framework organizes nearly 500 trends into 12 clear categories.
Within those categories are specific use cases and recommendations for
key roles in many organizations: strategy, innovation, R&D, and risk.
Each trend offers six important insights.
1. Years on the List 2. Key Insight 4. Disruptive Impact 6. Action Scale Informs Strategy
We track longitudinal tech and Concise description of this trend The implications of this trend on FTI’s analysis of what action your Strong evidence and data. Longer-
science trends. This measurement that can be easily understood and your business, government, or organization should take. Fields term uncertainties remain. Use it to
indicates how long we have repeated to others. society. include: inform your strategic planning.
followed the trend and its
progression. 3. Examples 5. Emerging Players Watch Closely Act Now
Real-world use cases, some of Individuals, research teams, Mounting evidence and data, but Ample evidence and data. This
which should be familiar to you. startups, and other organizations more maturity is needed. Use it to trend is already mature and
emerging in this space. inform your vision, planning, and requires action.
research.
04 © 2021 Future Today Institute
00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence Macro Forces and Emerging Trends Scenarios Describe Plausible Outcomes You will find scenarios imagining future worlds as trends evolve and converge. Scenarios offer a fresh perspective on trends and often chal- lenge your deeply held beliefs. They prompt you to consider high-impact, high-uncertainty situations using signals available today. 1 1. Headline 2 A short description offering you a glimpse into future changes. 2. Temporal and Emotive Tags 3 A label explaining both when in the future this scenario is set and whether it is optimistic, neutral, pessimistic, or catastrophic. 3. Narrative The descriptive elements of our imagined world, including the developments leading us to this point in our future history. Scenario sources: The Future Today Institute uses a wide array of quali- tative and quantitative data to create our scenarios. Some of our typical sources include patent filings, academic preprint servers, archival re- search, policy briefings, conference papers, data sets, structured inter- views with experts, conversations with kids, critical design, and specula- tive fiction. 05 © 2021 Future Today Institute
00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence
+ Natural language processing is + Natural language processing
an area experiencing high inter- algorithms— typically used for
est, investment, and growth. text, words, and sentences—are
being used to interpret genetic
+ No-code or low-code systems changes in viruses.
are unlocking new use cases for
Artificial
businesses. + COVID-19 accelerated the use of
AI in drug discovery last year. The
+ Amazon Web Services, Azure, first trial of an AI-discovered drug
and Google Cloud’s low-code is underway in Japan.
and no-code offerings will trickle
down to everyday people, al- + AI plays key roles in synthetic
lowing them to create their own biology, genetics, and medical
Intelligence
artificial intelligence applica- imaging; predicting the spread of
tions and deploy them as easily disease; and improving patient
as they could a website. health outcomes.
+ The race is on to capture AI + New artificial nervous systems
cloudshare—and to become the use AI and neural implants.
most trusted provider of AI on
Summary
remote servers. + The SuperGLUE benchmark,
which measures AI’s human
+ The AI community still operates language ability, will likely be
using a closed-source model. Re- surpassed by the end of 2021.
searchers’ reluctance to publish
their full code leads to less trans-
parency and reproducibility, and
makes accountability murky.
06 © 2021 Future Today Institute00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence
+ Gaussian processes, the gold + Technical alliances that help
standard for many real-world drive future R&D could also
modeling problems, are becom- challenge existing geopolitical
ing more accurate and easier alliances.
to train.
+ Future wars will be fought in
Artificial
+ AI researchers are leaving ac- code, using data and algorithms
ademia for corporations at an as powerful weapons.
alarming pace.
+ We continue to fail to see
+ Generative adversarial networks China’s growing AI proficiency
assist artists and musicians in as a military, economic, and
new forms of creative expression. diplomatic threat.
Intelligence
+ A new wave of AI nationalism is + New software could be viable for
rising as governments institute 100 years by using AI to adapt to
new restrictions on M&A and changes around it.
investment activity.
+ Several countries will launch
Summary
national AI strategies in 2021
and 2022.
+ New measures to regulate the
creation and distribution of
deepfakes will be introduced
throughout 2021 and 2022.
07 © 2021 Future Today Institute00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence Watch Closely Informs Strategy Act Now
14TH YEAR ON THE LIST
Artificial Intelligence
KEY INSIGHT EXAMPLES DISRUPTIVE IMPACT EMERGING PLAYERS
AI is now used across most industries. The convergence of groundbreaking • Broad Institute
Artificial intelligence It solves business problems, detects research, business use cases, the explosive • Clarifai
represents the third era fraud, improves crop yields, manages growth of data, and improvements in • Clearview AI
supply chains, recommends products, computing power and storage are en-
of computing, generally • DeepMind
and even assists designers and writers in abling advances in AI. The global artificial
defined as the ability their work. AI can predict call volume in intelligence market is expected to grow at • Disperse
for a machine to per- customer service centers and recommend a compound annual growth rate of 42.2% • Graphcore
staffing levels; it also predicts the emo- from 2021 to 2027. • HiSilicon Technologies
form cognitive functions tional state and behavior of the person • Kasisto
as well as or better than calling to help companies anticipate desir-
• LabGenius
humans. Such functions able solutions. AI automates the process
• Mohamed bin Zayed University
for drug discovery, which ultimately led
include perception, to faster COVID-19 vaccine candidates.
of Artificial Intelligence
• Niantic
learning, reasoning, Because AI is so broad, we have identified
different themes within the discipline • Nvidia
problem-solving, con- that you should be following. You will • OpenAI
textual understanding, also find the technology intersecting with • OpenMined
making inferences and other trends throughout this report.
• Persado
predictions, and exer- • PolyAI
cising creativity. • Recursion
AI is a force multiplier for every industry. • SenseTime
• Scale AI
• Syntiant
08 © 2021 Future Today Institute00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence Watch Closely Informs Strategy Act Now
An Executive’s Guide to AI
What You Need To Know Machine Learning teams know how to classify the input ing to learn about an environment (such themselves. For example, once a system
AI pioneer Arthur Samuel popularized data and what they are trying to predict as a complex financial portfolio), or when learns what an object looks like—say, an
In its most basic form, artificial intelli-
the idea of machine learning in 1959, but can get accurate results much more the researcher needs to find greater levels apple—it can recognize that object in all
gence is a system that makes autonomous
explaining how computers could learn quickly by relying on an algorithm rather of optimization. It has a tremendous other images, even if it has only a partial
decisions. AI is a branch of computer
without being explicitly programmed. than a human. Understanding what number of business use cases, ranging view.
science in which computers are pro-
This would mean developing an al- product features would most likely drive from real-time dynamic pricing models There are different types of deep learning
grammed to do things that normally
gorithm that could someday extract new purchases is an example of a busi- to high frequency trading algorithms to models. The most common types include
require human intelligence. This includes
patterns from datasets and use those ness use case for supervised learning. the systems that run self-driving cars. convolutional neural networks, recurrent
learning, reasoning, problem-solving,
understanding language, and perceiving patterns to predict and make real-time In unsupervised learning, data is pro- neural networks, transformer neural
a situation or environment. AI is an decisions automatically. It took many vided to an algorithm without specific Deep Learning networks, and generative adversarial
extremely large, broad field that uses years for reality to catch up with Samu- output parameters. For example, if a networks (GANs).
Deep learning is a relatively new branch
its own computer languages and relies el’s idea, but today machine learning is a researcher doesn’t know quite what to A convolutional neural network
of machine learning. Programmers use
on computer networks modeled on our primary driver of the growth in AI. do with a large dataset, an algorithm (CNN) is multilayered, with a convolu-
special deep learning algorithms along-
human brains. Machine learning uses data to make pre- could determine patterns, classify data, tional layer, a pooling layer, and a fully
side an enormous corpus of data—typ-
dictions and recommendations on how and make recommendations without a connected layer. Each one performs a
ically many terabytes of text, images,
to achieve stated goals. Types of machine human supervisor. Unsupervised learn- different task using the data. The output
videos, speech, and the like. Often, these
learning include supervised, unsuper- ing has been used during the pandemic to is classification. If a researcher has 10,000
systems are trained to learn on their
vised, and reinforcement. find patterns in how the virus is spread- images and needs to extract data—to rec-
own, and they can sort through a variety
ing throughout communities. ognize particular faces, for instance—the
In supervised learning, an algorithm of unstructured data, whether it’s making
uses training data to learn the relation- In reinforcement learning, an algo- sense of typed text in documents or audio CNN would run until information could
ship between established parameters— rithm learns to perform a task by repeat- clips or video. In practical terms, deep be inferred. In business, CNNs are used
inputs and outputs. Humans supervise, edly running calculations as it attempts to learning’s emergence means that more for recognition: anomalies in medical
tweaking and adjusting systems as they accomplish a stated goal. Reinforcement and more human processes will be auto- imaging, faulty products on a production
work. Supervised learning is used when learning is used when there isn’t enough mated, including the writing of software, line, blight on crops.
training data, when the researcher is try- which computers will soon start to do
09 © 2021 Future Today Institute00 01 02 03 04 05 06 07 08 09 10 11 12 Artificial Intelligence Watch Closely Informs Strategy Act Now
An Executive’s Guide to AI
Recurrent neural networks (RNNs) in the past year, are generated using Weak and Strong AI AI. This is problematic for researchers inforcement learning, in which machines
are multilayered neural networks that GANs. In design, GANs are tremendous- There are two kinds of AI—weak (or covering AI developments and for man- learn not unlike we do—by trial and
move and store information between ly useful: They can produce thousands “narrow”) and strong (or “general”). Nar- agers who must make decisions about error. While we haven’t seen an anthro-
input, hidden, and output layers. They of designs and recommend the best ones row AI systems make decisions within AI. In fact, we have already started to pomorphic AI walk out of DeepMind’s
are good at modeling sequence data for based on desired parameters. They can very narrow parameters at the same level see real-world examples of functioning lab, we should consider these projects
predictions. In business, they are used generate and modulate voices, faces, as a human or better, and we use them all artificial general intelligence. In 2017, as part of a long transition between the
anytime the sequence of data matters, even gestures. Researchers from Nvidia, day long without even realizing it. The researchers at DeepMind, a lab owned narrow AI of today and the strong AI of
such as speech recognition and language Massachusetts General Hospital, BWH anti-lock brakes in your car, the spam by the same parent company as Google, tomorrow.
translation. RNNs are used in digital Center for Clinical Data Science, and filter and autocomplete functions in announced that AI had taught itself how
assistants, to create captions for images, the Mayo Clinic collaborated on a GAN your email, and the fraud detection that to play chess, shogi (a Japanese version of
and to generate narrative reports using that generates synthetic MRIs showing authenticates you for a credit card pur- chess), and Go (an abstract strategy board
structured data (sports, financial). cancerous tumors. chase—these are all examples of artificial game)—all without any human inter-
GANs are unsupervised deep learning A transformer is a type of neural net- narrow intelligence. vention. The system, named AlphaZero,
systems composed of two competing work architecture that learns what words quickly became the strongest player in
Artificial general intelligence (AGI) de- history for each game. The team has
neural networks—a generator and a mean when they appear in a particular scribes systems capable of decision-mak-
discriminator—that are trained on the context. Using “attention mechanism,” a been publishing important discoveries at
ing outside of narrow specialties. Dolores an impressively fast pace. Last year, the
same data, such as images of people. The transformer looks at an input sequence in “Westworld,” the Samantha operating
networks compete against each other to and determines at each step what other DeepMind team taught AI agents to play
system in “Her,” and the H.A.L. super- complex games, such as the capture the
perform a task—identifying the correct parts of the sequence are important. To computer from “2001: A Space Odyssey”
person—which results in optimizing date, transformers have mainly been flag “game mode” inside the video game
are anthropomorphized representa- “Quake III Arena.” They, like humans,
overall performance. GANs are useful used in natural language processing and tions of AGI—but the actual technology
when researchers don’t have enough data generation. had learned skills specific to the game
doesn’t necessarily require humanlike as well as when and how to collaborate
to train an algorithmic model. They are appearances or voices.
also used to create new, synthetic data. with other teammates. The AI agents had
Deepfakes, which have become popular There is no single standard that marks matched human player ability using re-
the distinction between weak and strong
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