We may earn an affiliate commission when you visit our partners.

Digital Strategies

Managing Sociotechnological Co-Evolution

Martin Hilbert

Unravel the mysteries behind the accelerating pace of technological change, exploring mathematical principles and historical precedents behind AI and large learning models (LLM). Gain insights into the dichotomy of continuous innovation versus disruptive breakthroughs, and evaluate their profound impact on industries and economies worldwide. Investigate the societal implications of technological diffusion, analyzing inequalities and proposing viable policy solutions. Navigate the complex terrain of ethical considerations in technological advancement, addressing issues of bias, inclusivity, and AI alignment. Delve into the ethical frameworks guiding innovation, while contemplating the future of human-machine collaboration and the ethical imperatives therein.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

Two deals to help you save

Save money when you learn. Here are two deals and offers that may be relevant to this course.

All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid until December 2

Annual Subscription

Invest in your career growth and save. Start your annual subscription to Coursera Plus and access 10,000+ programs.

Valid until March 12, 2027

Save 40% Off 3 Months

Access thousands of top-rated learning programs with a Coursera Plus monthly subscription and take 40% off 3 months for a limited time.

What's inside

Syllabus

Getting Started and Defining Technology

After this module, you will be able to review how the social construction of technology requires proactive change management and be able to define what technology is and learn how this organismic system evolves. You'll be able to analyze the historical evolution of technology and its impact on society from the Stone Age to the digital age and develop a working definition of technology that allows you to understand its different aspects and roles in society. You'll also be able to discover why ‘things are getting faster and faster’, by exploring the mathematical logic behind the unavoidable accelerating nature of technological change.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores recent and ongoing technological advancements' societal and economic impacts

Examines the influence of exponential technological progress on industry and society

Develops critical thinking skills through the analysis of real-world case studies

Taught by Martin Hilbert, a leading expert in the field of technology and society

Provides a comprehensive overview of the evolution and impact of technology

Requires students to have a basic understanding of mathematics and technology

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.

Save

Reviews summary

Strategic insights on sociotechnological evolution

According to learners, this course offers incredibly insightful analysis of technological change, societal impact, and ethical considerations. Many found the content highly relevant to current industry challenges, particularly the modules on AI ethics, the digital divide, and disruptive innovation. It provides a strong theoretical foundation and historical context, with well-structured lectures. However, a few learners noted the pace can be fast and the content dense, suggesting it's best for those with some prior knowledge. Some also desired more practical application and case studies, feeling it leaned more theoretical.

Instructor lauded for clarity and passion in complex topics.

"The instructor's ability to simplify complex concepts while maintaining depth was remarkable."

"The instructor's passion for the subject shines through."

Provides a robust academic grounding in key concepts.

"A solid course covering essential aspects of socio-technological co-evolution."

"The historical context provided was excellent, and understanding Moore's Law in detail was beneficial."

"The course provides a strong theoretical foundation, some sections could benefit from more recent examples..."

"I enjoyed the historical evolution part and the insights into accelerating tech change. The course provides a solid foundation for understanding the macro trends."

Offers deep understanding crucial for current strategic roles.

"This course was incredibly insightful, especially the modules on AI ethics and the digital divide."

"The content felt highly relevant to current industry challenges."

"Excellent course! The material on disruptive innovation was particularly eye-opening."

"The course gave me a new lens through which to view digital strategy."

Some learners found content dense and pace challenging.

"The topics are interesting, but I found the pace a bit fast in some modules..."

"It felt like a lot of information was packed into a short time, making it hard to absorb fully without prior knowledge."

"Found this course quite challenging to follow. The content felt very dense and abstract, lacking practical examples..."

"I struggled with the rapid pace and dense theoretical discussions."

Course leans theoretical; some desire more hands-on cases.

"My only minor critique is that some discussions felt a bit theoretical at times, and I wished for more case studies or hands-on application scenarios."

"While the course provides a strong theoretical foundation, some sections could benefit from more recent examples..."

"I felt some parts were a bit too academic and less focused on direct application, which is what I was hoping for as a professional."

"I think it's probably better suited for academics or those with a very strong background in economics and technology theory."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Digital Strategies: Managing Sociotechnological Co-Evolution with these activities:

Read 'The Master Algorithm' by Pedro Domingos

Show steps

Gain insights into the fundamental concepts and challenges of AI by exploring a seminal text in the field.

View The Master Algorithm: How the Quest for the... on Amazon

Show steps

Read the book thoroughly, taking notes and highlighting key passages
Summarize the main arguments and implications of the book in a written report

Create a Comprehensive Course Resource Binder

Show steps

Organize and consolidate course materials for effective reference throughout your learning journey.

Show steps

Gather all course materials, including lecture notes, assignments, quizzes, and exams
Organize materials into logical sections or categories

Review Historical Context of Technological Evolution

Show steps

Brush up on the historical development of technology to provide context for the course material.

Browse courses on History of Technology

Show steps

Read chapters 1-3 of 'The Innovators' by Walter Isaacson
Watch the documentary 'The Silicon Valley Story'
Create a timeline of major technological advancements

Six other activities

Expand to see all activities and additional details

Show all nine activities

Practice Identifying Continuous and Disruptive Innovations

Show steps

Engage in exercises to sharpen your ability to distinguish between continuous and disruptive innovations.

Browse courses on Disruptive Innovation

Show steps

Analyze case studies of different innovations, categorizing them as continuous or disruptive
Participate in online quizzes or games testing your understanding of innovation types

Join a Study Group on Ethical Implications of AI

Show steps

Engage with peers to discuss and debate the ethical considerations surrounding AI.

Browse courses on Ethics of AI

Show steps

Find a study group or create your own with classmates or online
Facilitate discussions on topics such as AI bias, privacy concerns, and job displacement

Explore Online Tutorials on AI Alignment

Show steps

Enhance your understanding of AI alignment through structured online tutorials.

Browse courses on Responsible AI

Show steps

Identify reputable online platforms offering tutorials on AI alignment
Complete interactive exercises and simulations to practice AI alignment principles

Develop an Infographic on the Digital Divide

Show steps

Create a visual representation to illustrate the causes and consequences of the digital divide.

Browse courses on Digital Divide

Show steps

Research data on digital access, usage, and impact
Design and develop an infographic using a tool like Canva or Piktochart
Share your infographic on social media or a personal blog

Volunteer at a Technology Outreach Organization

Show steps

Gain practical experience in addressing technological inequalities by volunteering.

Browse courses on Community Engagement

Show steps

Research local organizations working to bridge the digital divide
Offer your skills in areas such as digital literacy training or technology maintenance

Contribute to an Open-Source AI Project

Show steps

Deepen your understanding of AI by contributing to open-source projects.

Browse courses on AI Development

Show steps

Identify open-source AI projects on platforms like GitHub or GitLab
Review project documentation and identify areas where you can contribute

Career center

Learners who complete Digital Strategies: Managing Sociotechnological Co-Evolution will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 35 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Digital Strategies: Managing Sociotechnological Co-Evolution.

Artificial Intelligence

Save

The definitive benchmark textbook of modern artificial intelligence, rigorously unifying search algorithms, probabilistic reasoning, knowledge representation, and machine learning into an elegant, coherent agent-based framework.

Artificial Intelligence: A Modern Approach

Hardcover

$$$$

Deep Learning

Save

A monumental foundational text establishing the mathematical, algorithmic, and statistical principles of modern deep neural networks, from linear algebra and optimization to convolutional and sequence modeling architectures.

Deep Learning (Adaptive Computation and Machine...

Hardcover

$$$

Deep Learning (Adaptive Computation and Machine...

Kindle Edition

$$$

Hands-On Machine Learning with Scikit-Learn, Keras,...

Save

Provides an exceptionally practical, code-first curriculum that guides engineers from end-to-end data preprocessing and traditional regression pipelines to production deep learning models and generative neural networks.

Digital Strategies

Two deals to help you save

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Strategic insights on sociotechnological evolution

Activities

Career center

Reading list

Share

Similar courses

Coursera Buyer Protection & Guarantee

7-Day Free Trial & Free Audit

14-Day Refund Guarantee

Verified Academic & Industry Partner