Connexion
Introducing children to computing concepts from a young age can help develop their interest and attachment to the subject. While parents might wonder what the best tools and resources are for this, primary and K1–5 educators also need to know what approaches work with their learners.
‘Teaching computing to 5- to 11-year-olds’ is one of the new course pathways we’ve designed to help educators spark young people’s interest in the subject. Our online courses are made by a team of writers, videographers, illustrators, animators, copy editors, presenters, and subject matter experts. They work together over months of production to create high-quality educational video content for participants all over the world.
This course pathway offers advice and practical activities to:
The nine courses included give you a comprehensive understanding of teaching computing to younger learners (5- to 11-year-olds). All the courses have been written by a team of subject matter experts, education professionals, and teachers. Some of the courses cover a specific topic, such as programming or physical computing, while others help educators reflect on their teaching practice.
All of the courses include a range of ideas to use in your own programming sessions. The activities will help you to introduce concepts like computer networks and the internet to young learners in a relatable way. There are also activities to help learners progress within a topic, such as moving from a block-based programming language like Scratch to a text-based one like Python.
The courses are an opportunity to:
These courses will give you everything you need to teach computing to young learners. No computing experience is required.
There is also no specific order in which you need to complete the courses. We want educators to complete the courses in an order that makes sense to them.
If you are new to teaching computing, ‘Get started teaching computing in primary schools’ is the place to start. The four-week course will encourage you to think about why it’s important for your learners to build their understanding around computing. You’ll discover how to support learners to become digital makers who can use technology to solve problems. Everyone who registers on the course will have access to an action plan to help implement what they have learnt into their teaching practice.
These are free courses for anyone, anywhere, who is interested in teaching young people about computing.
All of the courses take between two and four weeks to complete, based on participants spending two hours a week on a course. You will have free access to each course for the length of time it takes to complete it. For example, if it’s a two week course, like ‘Creating an inclusive classroom: approaches to supporting learners with SEND in computing’, you will have two weeks of free access to the course.
Discover what you could learn with ‘Teaching computing to 5- to 11-year-olds’ today.
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With our online courses programme, launched in 2017, we made it our mission to provide computing educators with the best possible free training we can design. Five years on, here are some of the key stats about the courses’ impact:
Designed and created in-house, each and every course is a real cross-team effort that involves a lot of careful planning and a number of different stages. Here we’re taking you behind the scenes to show you how we make our courses, introduce you to the people involved, and explain how we ensure our courses are of high quality.
But first, here’s some quick answers to questions you may have:
They are online training courses to help you learn about computing and computing education. The courses are hosted on the FutureLearn website. They are asynchronous, meaning you can take them whenever and wherever you want.
Yes! All our courses are free when you sign up for time-limited access, which gives you full access to the learning materials for the complete course duration. FutureLearn also has a paid-for ‘unlimited’ option, where you receive a certificate for each course you take.
They are aimed at educators, particularly classroom teachers, but they are also beneficial to anyone who wants to learn more about computing.
To help you structure your learning, our courses are divided into three or four weeks, but it’s up to you how quickly you work through them. You can complete a course in one afternoon, or spread your learning out and study for 30 minutes a day over three or four weeks. This flexibility makes it easy to fit a course into a busy schedule.
Creating our online courses is a team effort involving writers, videographers, illustrators, animators, copy editors, presenters, and subject matter experts working together over months of production. The entire process is guided by our online course producers, Martin O’Hanlon, Ross Exton, and Michael Conterio, who know a thing or two about creating high-quality learning experiences. We spoke to them about what it takes to create an engaging course.
Martin: We are driven by the needs of teachers. “What are teachers telling us they want to learn? Or what are the gaps in the curriculum where our learners need additional support?”
For example, our Introduction to Machine Learning and AI course was introduced as a result of feedback from teachers that while the subject wasn’t necessarily on the curriculum, they felt underprepared to answer questions from students or provide context when teaching other topics.
Michael: Working with the course authors, we’ll generally agree on the big topics we want to cover or questions that we want to answer. We’ll often also have individual elements that we want to fit in somewhere, for example an activity involving making a learning resource more accessible. From there it’s a case of taking the bigger topics and working out how we can split them up into smaller chunks, until we get down to individual learning activities.
Ross: But then we’ll end up shuffling things around until we are happy — not only that we’ve got everything that we wanted to cover, but that the overall structure makes sense. We often talk about the ‘narrative’ of a course.
Martin: At the Raspberry Pi Foundation we have a set of 12 pedagogy principles that we use through our learning resources (including online courses). We take particular care to lead with concepts, model processes, and activities; add variety for our learners; and include opportunities to create projects.
Michael: Because the learner is not present, you have to be incredibly precise with instructions as you can’t help learners directly as they are working through the content. And even if you think something is obvious, it’s easy for learners to accidentally miss an instruction, so it’s generally good to try to keep them together rather than spread out.
Martin: Luckily, it is often possible to tell from comments that learners have shared when something is hard to understand so we can improve future runs of the course.
Ross: It’s essential! It brings the abstract concepts of computing to life. The media in our courses helps our learners to visualise the ideas we’re presenting in ways that are engaging and relatable.
As we’re writing the course, we capture every creative idea that will best support our learners in gaining the knowledge and skills that they need. From ‘how-to’ guides with live coding, to physical computing demonstrations, or animations of robots, we think carefully about each image and video and how we’re not just telling the learner something, but showing them.
We then work with a brilliantly talented team of illustrators, animators, videographers, and presenters to create all of that media.
Ross: Social learning is a really important part of our online courses experience. Over the past year we have made significant investment to make it easier for participants to share programs they’ve written as part of their learning, for example, and for facilitators to provide support.
Martin: It is important people have the opportunity to share their learning with others. This is something often lost when taking an online course and it can feel like you are ‘on your own’.
In the Raspberry Pi Foundation’s online courses learners are given the opportunity to ask questions, share what they have created, and provide their own insight in the comments. Educators from the Foundation facilitate the courses — responding to comments and providing advice is a big part of what they do.
Thank you Martin, Michael, and Ross.
What new online course would you like us to create? Tell us in the comments below.
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Are you curious about coding and computer programming but don’t know how to begin? Do you want to help your children at home, or learners in your school, with their digital skills, but you’re not very confident yet? Then our new, free, and on-demand online course Introduction to Programming with Scratch course is a fun, creative, and colourful starting point for you.
Being able to code can help you do lots of things — from expressing yourself to helping others practice their skills, and from highlighting real-world issues to controlling a robot. Whether you want to get a taste of what coding is about, or you want to learn so that you can support young people, our Introduction to Programming with Scratch course is the perfect place to start if you’ve never tried any coding before.
On this on-demand course, Mark and Vasu from our team will help you take your very first steps on your programming journey.
On the course, you’ll use the programming language Scratch, a beginner-friendly, visual programming language particularly suitable for creating animations and games. All you need is our course and a computer or tablet with a web browser and internet connection that can access the online Scratch editor.
You can code in Scratch without having to memorise and type in commands. Instead, by snapping blocks together, you’ll take control of ‘sprites’, which are characters and objects on the screen that you can move around with the code you create.
As well as learning what you can do with Scratch, you’ll be learning basic programming concepts that are the same for all programming languages. You’ll see how the order of commands is important (sequencing), you’ll make the computer repeat actions (repetition), and you’ll write programs that do different things in different circumstances, for example responding to your user’s actions (selection). Later on, you’ll also make your own reusable code blocks (abstraction).
Throughout the course you’ll learn to make your own programs step by step. In the final week, Mark and Vasu will show you how you can create musical projects and interact with your program using a webcam.
Vasu and Mark will encourage you to share your programs and join the Scratch online community. You will discover how you can explore other people’s Scratch programs for inspiration and support, and how to build on the code they’ve created.
The course starts for the first time on Monday 14 February, but it is available on demand, so you can join it at any time. You’ll get four weeks’ access to the course no matter when you sign up.
For the first four weeks that the course is available, and every three months after that, people from our team will join in to support you and help answer your questions in the comments sections.
If you’re a teacher in England, get free extended access by signing up through Teach Computing here.
You can find more free resources here! These are the newest Scratch pathways on our project site, which you can also share with the young people in your life:
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Join our free online course Introduction to Machine Learning and AI to discover the fundamentals of machine learning and learn to train your own machine learning models using free online tools.
Although artificial intelligence (AI) was once the province of science fiction, these days you’re very likely to hear the term in relation to new technologies, whether that’s facial recognition, medical diagnostic tools, or self-driving cars, which use AI systems to make decisions or predictions.
By the end of this free, online, self-paced course, you will have an appreciation for what goes into machine learning and artificial intelligence systems — and why you should think carefully about what comes out.
You’ll also often hear about AI systems that use machine learning (ML). Very simply, we can say that programs created using ML are ‘trained’ on large collections of data to ‘learn’ to produce more accurate outputs over time. One rather funny application you might have heard of is the ‘muffin or chihuahua?’ image recognition task.
More precisely, we would say that a ML algorithm builds a model, based on large collections of data (the training data), without being explicitly programmed to do so. The model is ‘finished’ when it makes predictions or decisions with an acceptable level of accuracy. (For example, it rarely mistakes a muffin for a chihuahua in a photo.) It is then considered to be able to make predictions or decisions using new data in the real world.
But how does all this actually work? If you don’t know, it’s hard to judge what the impacts of these technologies might be, and how we can be sure they benefit everyone — an important discussion that needs to involve people from across all of society. Not knowing can also be a barrier to using AI, whether that’s for a hobby, as part of your job, or to help your community solve a problem.
For teachers and educators it’s particularly important to have a good foundational knowledge of AI and ML, as they need to teach their learners what the young people need to know about these technologies and how they impact their lives. (We’ve also got a free seminar series about teaching these topics.)
To help you understand the fundamentals of AI and ML, we’ve put together a free online course: Introduction to Machine Learning and AI. Over four weeks in two hours per week, learning at your own pace, you’ll find out how machine learning can be used to solve problems, without going too deeply into the mathematical details. You’ll also get to grips with the different ways that machines ‘learn’, and you will try out online tools such as Machine Learning for Kids and Teachable Machine to design and train your own machine learning programs.
As well as finding out how these AI systems work, you’ll look at the different types of tasks that they can help us address. One of these is classification — working out which group (or groups) something fits in, such as distinguishing between positive and negative product reviews, identifying an animal (or a muffin) in an image, or spotting potential medical problems in patient data.
You’ll also learn about other types of tasks ML programs are used for, such as regression (predicting a numerical value from a continuous range) and knowledge organisation (spotting links between different pieces of data or clusters of similar data). Towards the end of the course you’ll dive into one of the hottest topics in AI today: neural networks, which are ML models whose design is inspired by networks of brain cells (neurons).
Before an ML program can be trained, you need to collect data to train it with. During the self-paced course you’ll see how tools from statistics and data science are important for ML — but also how ethical issues can arise both when data is collected and when the outputs of an ML program are used.
By the end of the course, you will have an appreciation for what goes into machine learning and artificial intelligence systems — and why you should think carefully about what comes out.
The Introduction to Machine Learning and AI course is open for you to sign up to now. Sign-ups will pause after 12 December. Once you sign up, you’ll have access for six weeks. During this time you’ll be able to interact with your fellow learners, and before 25 October, you’ll also benefit from the support of our expert facilitators. So what are you waiting for?
As part of our research on computing education, we would like to find out about educators’ views on machine learning. Before you start the course, we will ask you to complete a short survey. As a thank you for helping us with our research, you will be offered the chance to take part in a prize draw for a £50 book token!
To develop your computing knowledge and skills, you might also want to:
If you are a teacher in England, you can develop your teaching skills through the National Centre for Computing Education, which will give you free upgrades for our courses (including Introduction to Machine Learning and AI) so you’ll receive certificates and unlimited access.
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Since 2017 we’ve been training Computing educators in England and around the world through our suite of free online courses on FutureLearn. Thanks to support from Google and the National Centre for Computing Education (NCCE), all of these courses are free for anyone to take, whether you are a teacher or not!
We’re excited that Computer Science educators at all stages in their computing journey have embraced our courses — from teachers just moving into the field to experienced educators looking for a refresher so that they can better support their colleagues.
Hear from two teachers about their experience of training with our courses and how they are benefitting!
Rebecca Connell started out as a Modern Foreign Languages teacher, but now she is Head of Computing at The Cowplain School, a 11–16 secondary school in Hampshire.
Although she had plenty of experience with Microsoft Office and was happy teaching IT, at first she was daunted by the technical nature of Computing:
“The biggest challenge for me has been the move away from an IT to a Computing curriculum. To say this has been a steep learning curve is an understatement!”
However, Rebecca has worked with our courses to improve her coding knowledge, especially in Python:
“Initially, I undertook some one-day programming courses in Python. Recently, I have found the Raspberry Pi courses to be really useful in building confidence and taking my skills further. So far, I have completed Programming 101 — great for revision and teaching ideas — and am now into Programming 102.”
GCSE Computing is more than just programming, and our courses are helping Rebecca develop the rest of her Computing knowledge too:
“I am now taking some online Raspberry Pi courses on computer systems and networks to firm up my knowledge — my greatest fear is saying something that’s not strictly accurate! These courses have some good ideas to help explain complex concepts to students.”
She also highly rates the new free Teach Computing Curriculum resources we have developed for the NCCE:
“I really like the new resources and supporting materials from Raspberry Pi — these have really helped me to look again at our curriculum. They are easy to follow and include everything you need to take students forward, including lesson plans.”
And Rebecca’s not the only one in her department who is benefitting from our courses and resources:
“Our department is supported by an excellent PE teacher who delivers lessons in Years 7, 8, and 9. She has enjoyed completing some of the Raspberry Pi courses to help her to deliver the new curriculum and is also enjoying her learning journey.”
Julie Price, a CAS Master Teacher and NCCE Computer Science Champion, has been “engaging with the NCCE’s Computer Science Accelerator programme, [to] be in a better position to appreciate and help to resolve any issues raised by fellow participants.”
“I have encountered new learning for myself and also expressions of very familiar content which I have found to be seriously impressive and, in some cases, just amazing. I must say that I am becoming addicted to the Raspberry Pi Foundation’s online courses!”
She’s been appreciating the open nature of the courses, as we make all of the materials free to use under the Open Government Licence:
“Already I have made very good use of a wide range of the videos, animations, images, and ideas from the Foundation’s courses.”
Julie particularly recommends the Programming Pedagogy in Secondary Schools: Inspiring Computing Teaching course, describing it as “a ‘must’ for anyone wishing to strengthen their key stage 3 programming curriculum.”
Rebecca and Julie are just 2 of more than 140,000 active participants we have had on our online courses so far!
With 29 courses to choose from (and more on the way!), from Introduction to Web Development to Robotics with Raspberry Pi, we have something for everyone — whether you’re a complete beginner or an experienced computer science teacher. All of our courses are free to take, so find one that inspires you, and let us support you on your computing journey, along with Google and the NCCE.
If you’re a teacher in England, you are eligible for free course certification from FutureLearn via the NCCE.
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At Raspberry Pi, we’re interested in all things to do with technology, from building new tools and helping people teach computing, to researching how young people learn to create with technology and thinking about the role tech plays in our lives and society. Today, I’m writing about our habit of replacing devices with newer versions just for the sake of it.
Technology is involved in more of our lives than ever before: most of us carry a computer in our pocket everywhere we go. On the other hand, the length of time for which we use each individual piece of technology has grown very short. This is what’s referred to as upgrade culture, a cycle which sees most of us replacing our most trusted devices every two years with the latest products offered by tech giants like Apple and Samsung.
How we got to this point is hard to determine, and there does not seem to be a single root cause for upgrade culture. This is why I want to start a conversation about it, so we can challenge our current perspectives and establish fact-based attitudes. I think it’s time that we, as individuals and as a collective, examine our relationship with new technology.
Digital technology is still so new that there is really no benchmark for how long digital devices should last. This means that the decision power has by default landed in the hands of device manufacturers and mobile network carriers, and for their profit margins, a two-year lifecycle of devices is beneficial.
Where do you see your role in this process as a consumer? Is it wrong to want to upgrade your phone after two years of constant use? Should phone companies slow their development, and would this hinder innovation? And, if you really need to upgrade, is there a better use for your old device than living in a drawer? These questions defy simple answers, and I want to hear what you think.
As with all our behaviours as consumers, the impact that upgrade culture has on the environment is an important concern. Environmental issues and climate change aren’t anything new, but they’re currently at the forefront of the global conversation, and for good reason.
Mobile devices are of course made in factories, and the concerns this raises have been covered well in many other places. The same goes for the energy needed to build technology. This energy could, at least in theory, be produced from renewable sources. Here I would like to focus on another aspect of the environmental impact device production has, which relates to the materials necessary to create the tiny components that form our technological best friends.
Some components of your phone cannot be created without rare chemical elements, such as europium and dysprosium. (In fact, there are 83 stable non-radioactive elements in the periodic table, and 70 of them are used in some capacity in your phone.) Upgrade culture means there is high demand for these materials, and deposits are becoming more and more depleted. If you’re hoping there are renewable alternatives, you’ll be disappointed: a study by researchers working at Yale University found that there are currently no alternative materials that are as effective.
Then there’s the issue of how the materials are mined. The market trading these materials is highly competitive, and more often than not manufacturers buy from the companies offer the lowest prices. To maintain their profit margin, these companies have to extract as much material as possible as cheaply as they can. As you can imagine, this leads to mining practices that are less than ethical or environmentally friendly. As many of the mines are located in distant areas of developing countries, these problems may feel remote to you, but they affect a lot of people and are a direct result of the market we are creating by upgrading our devices every two years.
Many of us agree that we need to do what we can to counteract climate change, and that, to achieve anything meaningful, we have to start looking at the way we live our lives. This includes questioning how we use technology. It will be through discussion and opinion gathering that we can start to make more informed decisions — as individuals and as a society.
You probably also have that one friend/colleague/family member who swears by their five year old mobile phone and scoffs at the prices of the newest models. These people are often labeled as sticklers who are afraid to join the modern age, but is there another way to see them? The truth is, if you’ve bought a phone in the last five years, then — barring major accidents — it will most likely still function and be just as effective as it was when it came out of the box. So why are so many consumers upgrading to new devices every two years?
Again there isn’t a single reason, but I think marketing departments should shoulder much of the responsibility. Using marketing strategies, device manufacturers and mobile network carriers purposefully make us see the phones we currently own in a negative light. A common trope of mobile phone adverts is the overwrought comparison of your current device with a newly launched version. Thus, each passing day after a new model is released, our opinion of our current device worsens, even if it’s just on a subconscious level.
This marketing strategy is related to a business practice called planned obsolescence, which sees manufacturers purposefully limit the durability of their products in order to sell more units. An early example of planned obsolescence is the lightbulb, invented at the Edison company: it was relatively simple for the company to create a lightbulb that lasted 2500 hours, but it took years and a coalition of manufacturers to make a version that reliably broke after 1000 hours. We’re all aware that the lightbulb revolutionised many aspects of life, but it turns out it also had a big influence on consumer habits and what we see as acceptable practices of technology companies.
The final aspect of the impact of upgrade culture that I want to examine relates to the digital divide. This term describes the societal gap between the people with access to, and competence with, the latest technology, and the people without these privileges. To be able to upgrade, say, your mobile phone to the latest model every two years, you either need a great degree of financial freedom, or you need to tie yourself to a 24-month contract that may not be easily within your means. As a society, we revere the latest technology and hold people with access to it in high regard. What does this say to people who do not have this access?
Inadvertently, we are widening the digital divide by placing more value on new technology than is warranted. Innovation is exciting, and commercial success is celebrated — but do you ever stop and ask who really benefits from this? Is your new phone really that much better than the old one, or could it be that you’re mostly just basking in feeling the social rewards of having the newest bit of kit?
Obviously, this blog post wouldn’t be complete if we didn’t share our perspective as a technology company as well. So here’s Raspberry Pi Trading CEO Eben Upton:
“Raspberry Pi tries very hard to avoid obsoleting older products. Obviously the latest Raspberry Pi 4 runs much faster than a Raspberry Pi 1 (something like forty times faster), but a Raspbian image we release today will run on the very earliest Raspberry Pi prototypes from the summer of 2011. Cutting customers off from software support after a couple of years is unethical, and bad for business in the long term: fool me once, shame on you; fool me twice, shame on me. The best companies respect their customers’ investment in their platforms, even if that investment happened far in the past.”
“What’s even more unusual about Raspberry Pi is that we aim to keep our products available for a long period of time. So you can’t just run a 2020 software build on a 2014 Raspberry Pi 1B+: you can actually buy a brand-new 1B+ to run it on.”
“We’re constantly working to reduce the environmental footprint of Raspberry Pi. If you look next to the USB connectors on Raspberry Pi 4, you’ll see a chunky black component. This is the reservoir capacitor, which prevents the 5V rail from dropping too far when a new USB device is plugged in. By using a polymer electrolytic capacitor, from our friends at Panasonic, we’ve been able to avoid the use of tantalum.”
“When we launched the official USB-C power supply for Raspberry Pi 4, one or two people on Twitter asked if we could eliminate the single-use plastic bag which surrounded the cable and plug assembly inside the box. Working with our partners at Kuantech, we found that we could easily do this for the white supplies, but not for the black ones. Why? Because when the box vibrates in transit, the plug scuffs against the case; this is visible on the black plastic, but not on the white.”
Raspberry Pi power supply with scuff mark
“So for now, if you want to eliminate single-use plastic, buy a white supply. In the meantime, we’ll be working to find a way (probably involving cunning origami) to eliminate plastic from the black supply.”
Time for you to discuss! I want to hear from you about upgrade culture.
Share your thoughts in the comments!
Upgrade culture is one of the topics for which we offer you a discussion forum on our free online course Impact of Technology. For educators, the course also covers how to facilitate classroom discussions about these topics, and a new course run has just begun — sign up today to take part for free!
The Impact of Technology online course is one of many courses developed by us with support from Google.
The post Is upgrade culture out of date? appeared first on Raspberry Pi.
At Raspberry Pi, we’re interested in all things to do with technology, from building new tools and helping people teach computing, to researching how young people learn to create with technology and thinking about the role tech plays in our lives and society. One of the aspects of technology I myself have been thinking about recently is algorithms.
Technology impacts our lives at the level of privacy, culture, law, environment, and ethics.
All kinds of algorithms — set series of repeatable steps that computers follow to perform a task — are running in the background of our lives. Some we recognise and interact with every day, such as online search engines or navigation systems; others operate unseen and are rarely directly experienced. We let algorithms make decisions that impact our lives in both large and small ways. As such, I think we need to consider the ethics behind them.
Ethics are rules of conduct that are recognised as acceptable or good by society. It’s easier to discuss the ethics of a specific algorithm than to talk about ethics of algorithms as a whole. Nevertheless, it is important that we have these conversations, especially because people often see computers as ‘magic boxes’: you push a button and something magically comes out of the box, without any possibility of human influence over what that output is. This view puts power solely in the hands of the creators of the computing technology you’re using, and it isn’t guaranteed that these people have your best interests at heart or are motivated to behave ethically when designing the technology.
Who creates the algorithms you use, and what are their motivations?
You should be critical of the output algorithms deliver to you, and if you have questions about possible flaws in an algorithm, you should not discount these as mere worries. Such questions could include:
Below, I give two concrete examples to show where ethics come into the creation and use of algorithms. If you know other examples (or counter-examples, feel free to disagree with me), please share them in the comments.
Part of the ‘magic box’ mental model is the idea that computers are cold instructions followers that cannot think for themselves — so how can they be biased?
Humans aren’t born biased: we learn biases alongside everything else, as we watch the way our family and other people close to us interact with the world. Algorithms acquire biases in the same way: the developers who create them might inadvertently add their own biases.
Humans can be biased, and therefore the algorithms they create can be biased too.
An example of this is a gang violence data analysis tool that the Met Police in London launched in 2012. Called the gang matrix, the tool held the personal information of over 300 individuals. 72% of the individuals on the matrix were non-white, and some had never committed a violent crime. In response to this, Amnesty International filed a complaint stating that the makeup of the gang matrix was influenced by police officers disproportionately labelling crimes committed by non-white individuals as gang-related.
We live in a content-rich society: there is much, much more online content than one person could possibly take in. Almost every piece of content we consume is selected by algorithms; the music you listen to, the videos you watch, the articles you read, and even the products you buy.
Some of you may have experienced a week in January of 2012 in which you saw a lot of either cute kittens or sad images on Facebook; if so, you may have been involved in a global social experiment that Facebook engineers performed on 600,000 of its users without their consent. Some of these users were shown overwhelmingly positive content, and others overwhelmingly negative content. The Facebook engineers monitored the users’ actions to gage how they responded. Was this experiment ethical?
In order to select content that is attractive to you, content algorithms observe the choices you make and the content you consume. The most effective algorithms give you more of the same content, with slight variation. How does this impact our beliefs and views? How do we broaden our horizons?
People generally don’t like making decisions; almost everyone knows the discomfort of indecision. In addition, emotions have a huge effect on the decisions humans make moment to moment. Algorithms on the other hand aren’t impacted by emotions, and they can’t be indecisive.
While algorithms are not immune to bias, in general they are way less susceptible to it than humans. And if a bias is identified in an algorithm, an engineer can remove the bias by editing the algorithm or changing the dataset the algorithm uses. The same cannot be said for human biases, which are often deeply ingrained and widespread in society.
As is true for all technology, algorithms can create new problems as well as solve existing problems.
That’s why there are more and less appropriate areas for algorithms to operate in. For example, using algorithms in policing is almost always a bad idea, as the data involved is recorded by humans and is very subjective. In objective, data-driven fields, on the other hand, algorithms have been employed very successfully, such as diagnostic algorithms in medicine.
I would love to hear what you think: this conversation requires as many views as possible to be productive. Share your thoughts on the topic in the comments! Here are some more questions to get you thinking:
Feel free to respond to other people’s comments and discuss the points they raise.
The ethics of algorithms is one of the topics for which we offer you a discussion forum on our free online course Impact of Technology. The course also covers how to facilitate classroom discussions about technology — if you’re an educator teaching computing or computer science, it is a great resource for you!
The Impact of Technology online course is one of many courses developed by us with support from Google.
The post Can algorithms be unethical? appeared first on Raspberry Pi.
Over the autumn term, we’ll be launching three brand-new, online courses on the FutureLearn platform. Wherever you are in the world, you can learn with us for free, thanks to support from Google.
The course presenters are Pi Towers residents Mark, Janina, and Eirini
The first new course is Design and Prototype Embedded Computer Systems, which will start on 28 October. In this course, you will discover the product design life cycle as you design your own embedded system!
You’ll investigate how the purpose of the system affects the design of the system, from choosing its components to the final product, and you’ll find out more about the design of an algorithm. You will also explore how embedded systems are used in the world around us. Book your place today!
What else would you expect us to call the sequel to Programming 101 and Programming 102? That’s right — we’ve made Programming 103: Saving and Structuring Data! The course will begin on 4 November, and you can reserve your place now.
Programming 103 explores how to use data across multiple runs of your program. You’ll learn how to save text and binary files, and how structuring data is necessary for programs to “understand” the data that they load. You’ll look at common types of structured files such as CSV and JSON files, as well as how you can connect to a SQL database to use it in your Python programs.
The third course, Introduction to Encryption and Cryptography, is currently in development, and therefore coming soon. In this course, you’ll learn what encryption is and how it was used in the past, and you’ll use the Caesar and Vigenère ciphers.
The Caesar cipher is a type of substitution cipher
You’ll also look at modern encryption and investigate both symmetric and asymmetric encryption schemes. The course also shows you the future of encryption, and it includes several practical encryption activities, which can be used in the classroom too.
If you’re a secondary school teacher in England, note that all of the above courses count towards your Computer Science Accelerator Programme certificate.
The very first group of teachers who earned Computer Science Accelerator Programme certificates: they got to celebrate their graduation at Google HQ in London.
What’s been your favourite online course this year? Tell us about it in the comments.
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