AI – career orientation
Overview
Insights into career options and profiles
Who “makes”AI?
The hashtag initiative #I_make_AI was launched in May 2024 to make jobs in the field of AI more visible. Through short video clips, students gain diverse and lively insights into who works on or with AI.
The questions answered in the short videos were formulated by students from all over Germany. In the videos, experts from diverse fields talk about their professional activities and background, career paths, fun at work, their favourite AI projects, team and working conditions.
Here is an example from Tasha Austin Crandall, a mathematician with a PhD in AI. Sje talks about her work teaching people about AI, developing helpful technologies and her favourite project, supporting women in the field of STEM and AI:
The playlists are constantly being updated. Click here for the YouTube channel (the video clips are in English and German)
In dialogue with AI experts: Virtual class chats
In Amazon Future Engineer's virtual class chats, students can talk directly to experts. The professionals share their individual career stories, provide insights into their professions and answer questions about career choices, possible obstacles, external support and much more. Public and individual class chats are offered; all are interactive and free of charge. Recorded class chats are also available for viewing, and teaching materials are provided for teachers to prepare for and follow up on the discussions. Read more here
Appcamps offers school classes a visit to the AWS Digital Builders Showroom in Munich. The aim is to make AI application cases tangible for students. The examples come from retail, sport, manufacturing and many other industries. Only available in German. Read more here
In a poster by the Institute of Engineering and Technology (IET) students quickly get an overview of the very different fields of applications for AI. You can have a look and download the poster here.
The sources mentioned are suitable as a general presentation of careers related to artificial intelligence or in connection with our teaching material First steps with AI and data analysis which introduces students to the concepts of big data and generative AI.
Can you study AI at university?
There is an ever-increasing number of degrees and study courses offering specialisations in the field of AI and machine learning. In addition, it is already becoming apparent that most university degrees in the fields of STEM and even the humanities can serve as a basis for careers and specialisations related to AI.
The series ‘#WE at DFKI’ introduces five women, their careers and their work at the German Research Center for Artificial Intelligence (DFKI).
Click the names to directly go to the interviews:
Lorena Göritz - Psychologist and Information Systems Researcher
Julia Mayer - Mathematician and researcher at DFKI Kaiserslautern
Mansi Sharma - Computer scientist and researcher at DFKI Saarbrücken
Dr Tanja Schneeberger - Psychologist and Senior Researcher at DFKI Berlin
Dr. Melya Boukheddimi - Senior Researcher in Robotics at DFKI Bremen
In ‘Experience AI – Lesson 6’, students explore a range of AI-related careers. They will hear from people working in the field of AI and consider how AI applications and machine learning can be used in areas that interest them. Free registration is required. Read more here
Note: Previews of the AI-related professions in the material can be seen in the video from minute 1:00.
The Primary Science Teaching Trust's ‘A Scientist Just Like Me’ programme has compiled short profiles of scientists working with AI and machine learning.
Here you can download the PDFs directly:
Artificial Intelligence Researcher – Krishna Mooroogen
Data Scientist – Dr. Fiona Reid
Machine Learning Scientist – Kaushik Hatti
Software Engineer – Rebecca Harding
The Data Scientist Pavithra Srinath works at The Trade Desk in London and talks about she approaches being a Data Scientist, what is challenging about it and reasons to working in thr field of data science.
In this rather in-depth webinar five panellists discuss their views and experiences on questions such as How do you get into AI? What’s it like to work in AI? What AI skills are in-demand? Can AI qualifications support career progression?
AI in vocational training
In vocational training, AI can be integrated in a versatile and interdisciplinary way into almost all professional fields.
One training occupation in which IT systems and machine learning are a direct part of the training is, of course, computer science. Witness a day with the trainees as IT specialists for system integration at Amazon:
A video tour through an Amazon logistics centre lets students discover how computer science, engineering and people work together. The 45-minute interactive tour explores how robotics, algorithms, machine learning, and more power the fulfilment process. It is suitable from age 8-17, including free accompanying material for teachers. Read more here
AI and sport
Data science, coding and AI have already found their way into the fields of sport and fitness, despite the ‘dusty’ clichés that may still exist here and there.
For example, Pearce Jarrett initially studied economy and is now a machine learning engineer and CEO. He has developed an AI-controlled app for personal training. Read more here or watch the following video:
AI experts can also be found in club and team sports: In the following video 'How is AI changing football?' (from DW - Digital World), experts show not only how important AI has become in football, but also how many professional opportunities the field offers outside of being an athlete. AI is part of modern game analysis, the technologies need to be programmed, trained and secured, video assistant referees (VAR) help analyze the data during a game and extensive research on the matter is being done at universities like the German Sport Universitiy in Cologne.
Watch the video here
In this article, sport informatics professor Daniel Link talks about data analysis at the European Football Championship 2024, the appeal of bringing AI and sport together, and the background of students participating in the Technical University of Munich's soccer hackathon.
To introduce students to the topic of machine learning and engage them with its application, explore our teaching materials for secondary school:
AI and sustainability
Scientists at DFKI (German Research Centre for Artificial Intelligence) explain which of the 17 sustainability goals of the United Nations are at the centre of their work with AI (English subtitles in the video).
“AI can be a transformational tool in our fight against climate change,” says Sims Witherspoon, leader at an AI research lab. She talks about how “AI can be a transformational tool in our fight against climate change” and discusses the importance of creating a carbon-free energy supply for powering AI applications.
Using AI in order to achieve sustainability is also central to two of our "AI in STEM Education" teaching resources: Primary students learn about recycling, becoming "EcoKids" in a role play introducing them to VR learning environments, educational robots and basic visual programming. And advanced secondary students can take on the challenge of constructing and coding a smart recycling system themselves.
AI and music
Working with AI and using it in a meaningful way already requires creativity in itself. But AI and computer science have also taken on an important role in traditional creative professions such as music production.
Amazon Music: Careers Behind the Beats contains various materials and interactive tours that highlight potential careers in the music industry: How does a song go from being recorded to being streamed on Amazon Music? How do people work together to develop or update a music streaming app? And which professions make all this possible? Read more here
The materials are part of the Your Voice is Power project which supports music, coding and initiative with teaching materials, scholarships, internships and competitions. Read more here
If students are interested in learning more about the music industry and how it is adapting to AI, the following episode of the podcast Offline with Jon Favreau might be of interest. It dives into questions of songwriting with AI in the future, how the music industry has historically adopted new technologies and how major record labels view AI. Listen by clicking on the following link:
'Why The Music Industry Is Embracing AI?' - Offline with Johan Favreau Podcast (54 min., 6/30/2024)
An introduction to AI music generators and further resources on ethical aspects, data and copyright protection are part of our teaching material First Steps in AI and Data Analysis (Activity 5): Read more here
AI, data science and machine learning – what are the differences?
How can you differentiate the fields of AI, data science and machine learning, and how do these differences spell out in the professional world?
The following interview with Chirag, a machine learning engineer at Airbnb, shows that machine learning has become an integral part of tourism:
In the interview below, Sreeta, data scientist at Uber, and Nikunj, machine learning engineer at Facebook (still called Facebook at the time of the interview), talk about the differences between their professions and discuss who has the “cooler” job:
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