Promotion material: Flyer
Credits: 5 EC
Motivation: Why is there a rush to AI? What is the role of cloud computing in the multi-trillion dollar valuation of tech companies? Are mobile phones really personal devices? How has the way software is produced today changed the theory and practice of computing? And, what are the implications of the technical breakthroughs pushed by big tech companies (Google, Apple, Facebook, Amazon and Microsoft (GAFAM)) for our societies? These are some of the questions we will ask during this course.
Synopsis: In the hands of GAFAM, software production has gone through fundamental changes that impact how computing and our society is organized. While Information and Communication Technologies (ICTs) have always been important for the functioning of public and private organizations, the turn to agile production with services based on current computational infrastructures (e.g., clouds, personal devices, (sensor) networks) organizes computing in a way that increases dependencies on the tech giants. These dependencies bring about significant changes that affect people, institutions and our common infrastructures (e.g., health, education, transportation, energy). These changes require a deeper understanding and a broader reflection as we implement digital services in all aspects of life using computational infrastructures dominated by GAFAM.
This course will walk you through prevalent changes in the production of software and the business of computing that transform our conception of computing and their impact on our societies. Throughout the course, you will find out about shifts in production and how (geo)political, economic and technological factors brought these into being. We will do so through case studies of turning points in the production of software and the associated computational infrastructures. We will study these turning points concretely in the context of GAFAMs. Examples of such turning points include the turn from personal computers to (mobile) devices attached to the clouds, waterfall methods to agile/lean methodologies, monolith architectures to (micro)services, instruction-based programming to AI, and the move from general-purpose to specialized chips.
Learning Outcomes: In this course you will discover how the way we produce software impacts how society is organized by reaching the following learning-objectives:
- Demonstrate a basic understanding of the history of computing through exemplary shifts in software production
- Compare the different roles big technology companies (Google, Apple, Facebook, Amazon, Microsoft shorthanded as GAFAM) play in providing current day computational infrastructures
- Illustrate how software production has become more dependent on computational infrastructures
- Reflect on the impact of new forms of software production on the capabilities of engineers, developers and scientists in designing and deploying systems
- Analyze and assess different privacy concerns, and corresponding privacy technologies that arise with shifts in software production
- Explain how the rise of ML/AI technologies are related to computational infrastructures
- Speculate and predict possible futures of software production in the hands of GAFAM
Lecturers: Dr. Seda Gürses (TUD) and Prof. Dr. Michel van Eeten (TUD)
Examination: 10% engagement, 50% 5 assignments; 40% oral exam.
The total of the assignments as well as the oral exam must be graded with at least 5.0. The final grade consists of the average of the three parts (engagement, assignments and exam), and the rounded grade must be at least 6.0 (5.75 rounded up).
Contents: During the course, you will learn how specific shifts in computing and software production aim to reconfigure organizations and how this is tied to the ever-growing business of computing dominated by GAFAM. Examples of such turning points include the turn from personal computers to (mobile) devices attached to the clouds, waterfall methods to agile/lean methodologies, monolith architectures to (micro)services, instruction-based programming to AI, and the move from general-purpose to specialized chips. As importantly, we will reflect on what this new form of production means for developers, engineers and (computer) scientists and the potentials and constraints it imposes on our ability to design systems. To be able to draw a comparison, we will look at how each shift in software production changes associated privacy concerns and how big tech companies have proposed to address them through privacy-by-design.
Core text: Various academic texts, videos, and grey material from the computing industry.