Technology transforms the world in so many ways. Ford’s introduction of the assembly line was essential to the vehicle manufacturing process. The introduction of the internet changed how we communicate, do business, and interact with the world. And in machine learning, we have an emerging technology that transforms how we use computers to complete complex tasks.
Think of machine learning models as “brains” that machines use to actively learn. No longer constrained by rules laid out in their programming, machines have the ability to develop an understanding of new concepts and deliver analysis in ways they never could before. And as a prospective machine learning student, you can become the person who creates the “brains” that modern machines use now and in the future.
But you need a good starting point before you can do any of that. This article covers three of the best machine learning tutorials for beginners who want to get their feet wet while building foundational knowledge that serves them in more specialized courses.
Factors to Consider When Choosing a Machine Learning Tutorial
A machine learning beginner can’t expect to jump straight into a course that delves into neural networking and deep learning and have any idea what they’re doing. They need to learn to crawl before they can walk, making the following factors crucial to consider when choosing a machine learning tutorial for beginners.
- Content quality. You wouldn’t use cheap plastic parts to build an airplane, just like you can’t rely on poor-quality course content to get you started with machine learning. Always look for reviews of a tutorial before engaging, in addition to checking the credentials of the provider to ensure they deliver relevant content that aligns with your career goals.
- Instructor expertise. Sticking with our airplane analogy, imagine being taught how to pilot a plane by somebody who’s never actually flown. It simply wouldn’t work. The same goes for a machine learning tutorial, as you need to see evidence that your instructor does more than parrot information that you can find elsewhere. Look for real-world experience and accreditation from recognized authorities.
- Course structure and pacing. As nice as it would be to have an infinite amount of free time to dedicate to learning, that isn’t a reality for anybody. You have work, life, family, and possibly other study commitments to keep on top of, and your machine learning tutorial has to fit around all of it.
- Practical and real-world examples. Theoretical knowledge can only take you so far. You need to know how to apply what you’ve learned, which is why a good tutorial should have practical elements that test your knowledge. Think of it like driving a car. You can read pages upon pages of material on how to drive properly but you won’t be able to get on the road until you’ve spent time learning behind the wheel.
- Community support. Machine learning is a complex subject and it’s natural to feel a little lost with the materials in many tutorials. A strong community gives you a resource base to lean into, in addition to exposing you to peers (and experienced tech-heads) who can help you along or point you in the right career direction.
Top Three Machine Learning Tutorials for Beginners
Now you know what to look for in a machine learning tutorial for beginners, you’re ready to start searching for a course. But if you want to take a shortcut and jump straight into learning, these three courses are superb starting points.
Tutorial 1 – Intro to Machine Learning (Kaggle)
Offered at no cost, Intro to Machine Learning is a three-hour self-paced course that allows you to learn as and when you feel like learning. All of which is helped by Kaggle’s clever save system. You can use it to save your progress and jump back into your learning whenever you’re ready. The course has seven lessons, the first of which offers an introduction to machine learning as a concept. Whereas the other six dig into more complex topics and come with an exercise for you to complete.
Those little exercises are the tutorial’s biggest plus point. They force you to apply what you’ve learned before you can move on to the next lesson. The course also has a dedicated community (led by tutorial creator Dan Becker) that can help you if you get stuck. You even get a certificate for completing the tutorial, though this certificate isn’t as prestigious as one that comes from an organization like Google or IBM.
On the downside, the course isn’t a complete beginner’s course. You’ll need a solid understanding of Python before you get started. Those new to coding should look for Python courses first or they’ll feel lost when the tutorial starts throwing out terminology and programming libraries that they need to use.
Ideal for students with experience in Python who want to apply the programming language to machine learning models.
Tutorial 2 – What Is Machine Learning? (Udemy)
You can’t build a house without any bricks and you can’t build a machine learning model before you understand the different types of learning that underpin that model. Those different types of learning are what the What is Machine Learning tutorial covers. You’ll get to grips with supervised, unsupervised, and reinforcement learning, which are the three core learning types a machine can use to feed its “brain.”
The course introduces you to real-world problems and helps you to see which type of machine learning is best suited to solving those problems. It’s delivered via online videos, totaling just under two hours of teaching, and includes demonstrations in Python to show you how each type of learning is applied to real-world models. All the resources used for the tutorial are available on a GitHub page (which also gives you access to a strong online community) and the tutorial is delivered by an instructor with over 27 years of experience in the field.
It’s not the perfect course, by any means, as it focuses primarily on learning types without digging much deeper. Those looking for a more in-depth understanding of the algorithms used in machine learning won’t find it here, though they will build foundational knowledge that helps them to better understand those algorithms once they encounter them. As an Udemy course, it’s free to take but requires a subscription to the service if you want a certificate and the ability to communicate directly with the course provider.
Ideal for students who want to learn about the different types of machine learning and how to use Python to apply them.
Tutorial 3 – Machine Learning Tutorial (Geeksforgeeks)
As the most in-depth machine learning tutorial for beginners, the Geeksforgeeks offering covers almost all of the theory you could ever hope to learn. It runs the gamut from a basic introduction to machine learning through to advanced concepts, such as natural language processing and neural networks. And it’s all presented via a single web page that acts like a hub that links you to many other pages, allowing you to tailor your learning experience based on what aligns best with your goals.
The sheer volume of content on offer is the tutorial’s biggest advantage, with dedicated learners able to take themselves from complete machine learning newbies to accomplished experts if they complete everything. There’s also a handy discussion board that puts you in touch with others taking the course. Plus, the “Practice” section of the tutorial includes real-world problems, including a “Problem of the Day” that you can use to test different skills.
However, some students may find the way the material is presented to be a little disorganized and it’s easy to lose track of where you are among the sea of materials. The lack of testing (barring the two or three projects in the “Practice” section) may also rankle with those who want to be able to track their progress easily.
Ideal for self-paced learners who want to be able to pick and choose what they learn and when they learn it.
Additional Resources for Learning Machine Learning
Beyond tutorials, there are tons of additional resources you can use to supplement your learning. These resources are essential for continuing your education because machine learning is an evolving concept that changes constantly.
- Books. Machine learning books are great for digging deeper into the theory you learn via a tutorial, though they come with the downside of offering no practical examples or ways to interact with authors.
- YouTube channels. YouTube videos are ideal for visual learners and they tend to offer a free way to build on what you learn in a tutorial. Examples of great channels to check out include Sentdex and DeepLearningAI, with both channels covering emerging trends in the field alongside lectures and tutorials.
- Blogs and websites. Blogs come with the advantage of the communities that sprout up around them, which you can rely on to build connections and further your knowledge. Of course, there’s the information shared in the blogs, too, though you must check the writer’s credentials before digging too deep into their content.
Master a Machine Learning Tutorial for Beginners Before Moving On
A machine learning tutorial for beginners can give you a solid base in the fundamentals of an extremely complex subject. With that base established, you can build up by taking other courses and tutorials that focus on more specialized aspects of machine learning. Without the base, you’ll find the learning experience much harder. Think of it like building a house – you can’t lay any bricks until you have a foundation in place.
The three tutorials highlighted here give you the base you need (and more besides), but it’s continued study that’s the key to success for machine learning students. Once you’ve completed a tutorial, look for books, blogs, YouTube channels, and other courses that help you keep your knowledge up-to-date and relevant in an ever-evolving subject.
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From the same author
Read the articleThe Open Institute of Technology (OPIT) is the perfect place for those looking to master the core skills and gain the fundamental knowledge they need to enter the exciting and dynamic environment of the tech industry. While OPIT’s various degrees and courses unlock the doors to numerous careers, students may not know exactly which line of work they wish to enter, or how, exactly, to take the next steps.
That’s why, as well as providing exceptional online education in fields like Responsible AI, Computer Science, and Digital Business, OPIT also offers an array of career-related services, like the Peer Career Mentoring Program. Designed to provide the expert advice and support students need, this program helps students and alumni gain inspiration and insight to map out their future careers.
Introducing the OPIT Peer Career Mentoring Program
As the name implies, OPIT’s Peer Career Mentoring Program is about connecting students and alumni with experienced peers to provide insights, guidance, and mentorship and support their next steps on both a personal and professional level.
It provides a highly supportive and empowering space in which current and former learners can receive career-related advice and guidance, harnessing the rich and varied experiences of the OPIT community to accelerate growth and development.
Meet the Mentors
Plenty of experienced, expert mentors have already signed up to play their part in the Peer Career Mentoring Program at OPIT. They include managers, analysts, researchers, and more, all ready and eager to share the benefits of their experience and their unique perspectives on the tech industry, careers in tech, and the educational experience at OPIT.
Examples include:
- Marco Lorenzi: Having graduated from the MSc in Applied Data Science and AI program at OPIT, Marco has since progressed to a role as a Prompt Engineer at RWS Group and is passionate about supporting younger learners as they take their first steps into the workforce or seek career evolution.
- Antonio Amendolagine: Antonio graduated from the OPIT MSc in Applied Data Science and AI and currently works as a Product Marketing and CRM Manager with MER MEC SpA, focusing on international B2B businesses. Like other mentors in the program, he enjoys helping students feel more confident about achieving their future aims.
- Asya Mantovani: Asya took the MSc in Responsible AI program at OPIT before taking the next steps in her career as a Software Engineer with Accenture, one of the largest IT companies in the world, and a trusted partner of the institute. With a firm belief in knowledge-sharing and mutual support, she’s eager to help students progress and succeed.
The Value of the Peer Mentoring Program
The OPIT Peer Career Mentoring Program is an invaluable source of support, inspiration, motivation, and guidance for the many students and graduates of OPIT who feel the need for a helping hand or guiding light to help them find the way or make the right decisions moving forward. It’s a program built around the sharing of wisdom, skills, and insights, designed to empower all who take part.
Every student is different. Some have very clear, fixed, and firm objectives in mind for their futures. Others may have a slightly more vague outline of where they want to go and what they want to do. Others live more in the moment, focusing purely on the here and now, but not thinking too far ahead. All of these different types of people may need guidance and support from time to time, and peer mentoring provides that.
This program is also just one of many ways in which OPIT bridges the gaps between learners around the world, creating a whole community of students and educators, linked together by their shared passions for technology and development. So, even though you may study remotely at OPIT, you never need to feel alone or isolated from your peers.
Additional Career Services Offered by OPIT
The Peer Career Mentoring Program is just one part of the larger array of career services that students enjoy at the Open Institute of Technology.
- Career Coaching and Support: Students can schedule one-to-one sessions with the institute’s experts to receive insightful feedback, flexibly customized to their exact needs and situation. They can request resume audits, hone their interview skills, and develop action plans for the future, all with the help of experienced, expert coaches.
- Resource Hub: Maybe you need help differentiating between various career paths, or seeing where your degree might take you. Or you need a bit of assistance in handling the challenges of the job-hunting process. Either way, the OPIT Resource Hub contains the in-depth guides you need to get ahead and gain practical skills to confidently move forward.
- Career Events: Regularly, OPIT hosts online career event sessions with industry experts and leaders as guest speakers about the topics that most interest today’s tech students and graduates. You can join workshops to sharpen your skills and become a better prospect in the job market, or just listen to the lessons and insights of the pros.
- Internship Opportunities: There are few better ways to begin your professional journey than an internship at a top-tier company. OPIT unlocks the doors to numerous internship roles with trusted institute partners, as well as additional professional and project opportunities where you can get hands-on work experience at a high level.
In addition to the above, OPIT also teams up with an array of leading organizations around the world, including some of the biggest names, including AWS, Accenture, and Hype. Through this network of trust, OPIT facilitates students’ steps into the world of work.
Start Your Study Journey Today
As well as the Peer Career Mentoring Program, OPIT provides numerous other exciting advantages for those who enroll, including progressive assessments, round-the-clock support, affordable rates, and a team of international professors from top universities with real-world experience in technology. In short, it’s the perfect place to push forward and get the knowledge you need to succeed.
So, if you’re eager to become a tech leader of tomorrow, learn more about OPIT today.
Read the articleThe world has entered the age of artificial intelligence (AI), and this exciting new technology is already changing the face of society in an ever-growing number of ways. It’s influencing a plethora of industries and sectors, from healthcare and education to finance and urban planning. This guide explores AI’s impact on three of the core pillars of life: business, education, and sustainability.
AI in Business: Unlocking Unprecedented Opportunities
In the world of business, the number of uses of AI is growing by the day. Whether it’s in sales, marketing, customer relations, operational optimization, cybersecurity, data management, or some other aspect of organizational life, there are so many ways this technology can unlock new opportunities or expedite existing processes.
Take data as an example. Many businesses now collect and use large amounts of data to inform their decisions in areas like product development or marketing strategy. But they have, up to now, been limited in how they can structure, visualize, and analyze their data. AI changes all that, as it can dig into vast databases with ease, extracting insights to drive actionable decisions in no time.
AI also bridges gaps in communications. It has the power to speak in most major languages, translating audio or written text with astonishing accuracy in an instant. In a globalized world, where many businesses buy and sell with partners, suppliers, investors, and other stakeholders from other nations, AI can help them communicate and exchange information more easily and reliably.
AI in Education: Democratizing and Accelerating the Learning Process
In the educational sector, AI is solving problems that have plagued this industry for generations and transforming the ways in which students learn and teachers teach. It can be used, for example, to personalize a student’s learning plan or adapt content to align with each learner’s favored learning style, making it easier for them to soak up and retain information and skills.
AI’s generative capabilities are also proving useful in the education sector. Teachers, for example, can turn to generative AI models to create lesson plans or supplementary content to support their courses, such as tables, charts, infographics, and images. This all helps to make the learning experience more diverse, dynamic, and engaging for every kind of learner.
On a broader level, there’s clear potential for AI to democratize education across the globe, making learning more accessible to all. That includes those in developing nations who may normally lack opportunities to gain knowledge and skills to achieve their ambitions. If harnessed correctly and responsibly, this technology could elevate education to whole new heights.
AI in Sustainability: Smarter Cities and Next-Level Efficiency
Sustainability is one of the sticking points when talking about AI, as many critics of the technology point to the fact that it involves huge amounts of energy and relies heavily on large and costly data centers to operate. At the same time, AI could also solve many of the sustainability crises facing the world today, uncovering solutions and innovations that may have previously taken decades to develop.
It’s already proving its value in this domain. For instance, DeepMind developed an AI system that was actually able to optimize data center energy efficiency, cutting the amount of energy used to cool data center hardware by a whopping 40% and improving energy efficiency in certain centers by 15%. That’s just one example, and it’s only the start of what AI could do from an environmental perspective.
This tech is also making cities smarter, more efficient, and more pleasant in which to live through AI-powered navigation aids or traffic redistribution systems. It also holds potential for future urban planning, city development, and infrastructure construction, provided the correct systems and frameworks can be established to make the best use of AI’s advantages.
The Ethical Challenges and Risks of AI
Despite its almost countless advantages and possible applications, AI is not without its flaws. This technology brings challenges and risks to go along with its opportunities, and five leading examples include:
- Bias: Algorithmic bias is an issue that has already presented itself during the relatively brief existence of AI so far. Some systems, for example, have issued responses or generated content that could be classified as discriminatory or prejudiced, due to the training data they were given.
- Privacy: There are fears among populations and analysts about the amount of data being fed into AI systems and how such data could be misused, potentially violating people’s rights of privacy and falling foul of data privacy regulations, such as GDPR.
- Misuse: Like so many game-changing technologies, AI has the potential to be used for both benevolent and malicious purposes. It may be used to spread misinformation and “fake news,” influence public opinion, or even in cyber-attacks, for instance.
- Over-reliance: AI is so powerful, with the capacity to carry out tasks with remarkable precision and speed, that it will be tempting for organizations to integrate it into many of their workflows and decision-making processes. But AI cannot be treated as a substitute for human judgment.
- Sustainability: There are also fears about the energy costs associated with AI and the data centers needed to power it, plus the fact that some elements of the burgeoning AI industry may exploit workers in poorer nations worldwide.
Solving These Challenges: Regulation and Responsible Use of AI
With the right approach, it is possible to solve all the above challenges, and more, making AI the most valuable and beneficial new technology the world has seen since the advent of the internet. This will require a two-pronged strategy focusing on both regulation and responsible usage.
Europe is already leading the way in the first aspect. It has introduced the AI Act – a world-first regulatory framework related to artificial intelligence, laying out how it should be used to drive innovation without infringing on the fundamental rights of workers and the larger public.
Educational institutions like the OPIT – Open Institute of Technology are also leading the way in the second aspect, educating people around the world on how to work with AI in a responsible, ethical way, through programs like the MSc in Responsible Artificial Intelligence.
By establishing rules and regulations about AI’s usage and educating the tech leaders of tomorrow in how to work with AI in a fair and responsible way, the future is bright for this exciting and extraordinary new technology.
-
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Related posts
The Open Institute of Technology (OPIT) is the perfect place for those looking to master the core skills and gain the fundamental knowledge they need to enter the exciting and dynamic environment of the tech industry. While OPIT’s various degrees and courses unlock the doors to numerous careers, students may not know exactly which line of work they wish to enter, or how, exactly, to take the next steps.
That’s why, as well as providing exceptional online education in fields like Responsible AI, Computer Science, and Digital Business, OPIT also offers an array of career-related services, like the Peer Career Mentoring Program. Designed to provide the expert advice and support students need, this program helps students and alumni gain inspiration and insight to map out their future careers.
Introducing the OPIT Peer Career Mentoring Program
As the name implies, OPIT’s Peer Career Mentoring Program is about connecting students and alumni with experienced peers to provide insights, guidance, and mentorship and support their next steps on both a personal and professional level.
It provides a highly supportive and empowering space in which current and former learners can receive career-related advice and guidance, harnessing the rich and varied experiences of the OPIT community to accelerate growth and development.
Meet the Mentors
Plenty of experienced, expert mentors have already signed up to play their part in the Peer Career Mentoring Program at OPIT. They include managers, analysts, researchers, and more, all ready and eager to share the benefits of their experience and their unique perspectives on the tech industry, careers in tech, and the educational experience at OPIT.
Examples include:
- Marco Lorenzi: Having graduated from the MSc in Applied Data Science and AI program at OPIT, Marco has since progressed to a role as a Prompt Engineer at RWS Group and is passionate about supporting younger learners as they take their first steps into the workforce or seek career evolution.
- Antonio Amendolagine: Antonio graduated from the OPIT MSc in Applied Data Science and AI and currently works as a Product Marketing and CRM Manager with MER MEC SpA, focusing on international B2B businesses. Like other mentors in the program, he enjoys helping students feel more confident about achieving their future aims.
- Asya Mantovani: Asya took the MSc in Responsible AI program at OPIT before taking the next steps in her career as a Software Engineer with Accenture, one of the largest IT companies in the world, and a trusted partner of the institute. With a firm belief in knowledge-sharing and mutual support, she’s eager to help students progress and succeed.
The Value of the Peer Mentoring Program
The OPIT Peer Career Mentoring Program is an invaluable source of support, inspiration, motivation, and guidance for the many students and graduates of OPIT who feel the need for a helping hand or guiding light to help them find the way or make the right decisions moving forward. It’s a program built around the sharing of wisdom, skills, and insights, designed to empower all who take part.
Every student is different. Some have very clear, fixed, and firm objectives in mind for their futures. Others may have a slightly more vague outline of where they want to go and what they want to do. Others live more in the moment, focusing purely on the here and now, but not thinking too far ahead. All of these different types of people may need guidance and support from time to time, and peer mentoring provides that.
This program is also just one of many ways in which OPIT bridges the gaps between learners around the world, creating a whole community of students and educators, linked together by their shared passions for technology and development. So, even though you may study remotely at OPIT, you never need to feel alone or isolated from your peers.
Additional Career Services Offered by OPIT
The Peer Career Mentoring Program is just one part of the larger array of career services that students enjoy at the Open Institute of Technology.
- Career Coaching and Support: Students can schedule one-to-one sessions with the institute’s experts to receive insightful feedback, flexibly customized to their exact needs and situation. They can request resume audits, hone their interview skills, and develop action plans for the future, all with the help of experienced, expert coaches.
- Resource Hub: Maybe you need help differentiating between various career paths, or seeing where your degree might take you. Or you need a bit of assistance in handling the challenges of the job-hunting process. Either way, the OPIT Resource Hub contains the in-depth guides you need to get ahead and gain practical skills to confidently move forward.
- Career Events: Regularly, OPIT hosts online career event sessions with industry experts and leaders as guest speakers about the topics that most interest today’s tech students and graduates. You can join workshops to sharpen your skills and become a better prospect in the job market, or just listen to the lessons and insights of the pros.
- Internship Opportunities: There are few better ways to begin your professional journey than an internship at a top-tier company. OPIT unlocks the doors to numerous internship roles with trusted institute partners, as well as additional professional and project opportunities where you can get hands-on work experience at a high level.
In addition to the above, OPIT also teams up with an array of leading organizations around the world, including some of the biggest names, including AWS, Accenture, and Hype. Through this network of trust, OPIT facilitates students’ steps into the world of work.
Start Your Study Journey Today
As well as the Peer Career Mentoring Program, OPIT provides numerous other exciting advantages for those who enroll, including progressive assessments, round-the-clock support, affordable rates, and a team of international professors from top universities with real-world experience in technology. In short, it’s the perfect place to push forward and get the knowledge you need to succeed.
So, if you’re eager to become a tech leader of tomorrow, learn more about OPIT today.
The world has entered the age of artificial intelligence (AI), and this exciting new technology is already changing the face of society in an ever-growing number of ways. It’s influencing a plethora of industries and sectors, from healthcare and education to finance and urban planning. This guide explores AI’s impact on three of the core pillars of life: business, education, and sustainability.
AI in Business: Unlocking Unprecedented Opportunities
In the world of business, the number of uses of AI is growing by the day. Whether it’s in sales, marketing, customer relations, operational optimization, cybersecurity, data management, or some other aspect of organizational life, there are so many ways this technology can unlock new opportunities or expedite existing processes.
Take data as an example. Many businesses now collect and use large amounts of data to inform their decisions in areas like product development or marketing strategy. But they have, up to now, been limited in how they can structure, visualize, and analyze their data. AI changes all that, as it can dig into vast databases with ease, extracting insights to drive actionable decisions in no time.
AI also bridges gaps in communications. It has the power to speak in most major languages, translating audio or written text with astonishing accuracy in an instant. In a globalized world, where many businesses buy and sell with partners, suppliers, investors, and other stakeholders from other nations, AI can help them communicate and exchange information more easily and reliably.
AI in Education: Democratizing and Accelerating the Learning Process
In the educational sector, AI is solving problems that have plagued this industry for generations and transforming the ways in which students learn and teachers teach. It can be used, for example, to personalize a student’s learning plan or adapt content to align with each learner’s favored learning style, making it easier for them to soak up and retain information and skills.
AI’s generative capabilities are also proving useful in the education sector. Teachers, for example, can turn to generative AI models to create lesson plans or supplementary content to support their courses, such as tables, charts, infographics, and images. This all helps to make the learning experience more diverse, dynamic, and engaging for every kind of learner.
On a broader level, there’s clear potential for AI to democratize education across the globe, making learning more accessible to all. That includes those in developing nations who may normally lack opportunities to gain knowledge and skills to achieve their ambitions. If harnessed correctly and responsibly, this technology could elevate education to whole new heights.
AI in Sustainability: Smarter Cities and Next-Level Efficiency
Sustainability is one of the sticking points when talking about AI, as many critics of the technology point to the fact that it involves huge amounts of energy and relies heavily on large and costly data centers to operate. At the same time, AI could also solve many of the sustainability crises facing the world today, uncovering solutions and innovations that may have previously taken decades to develop.
It’s already proving its value in this domain. For instance, DeepMind developed an AI system that was actually able to optimize data center energy efficiency, cutting the amount of energy used to cool data center hardware by a whopping 40% and improving energy efficiency in certain centers by 15%. That’s just one example, and it’s only the start of what AI could do from an environmental perspective.
This tech is also making cities smarter, more efficient, and more pleasant in which to live through AI-powered navigation aids or traffic redistribution systems. It also holds potential for future urban planning, city development, and infrastructure construction, provided the correct systems and frameworks can be established to make the best use of AI’s advantages.
The Ethical Challenges and Risks of AI
Despite its almost countless advantages and possible applications, AI is not without its flaws. This technology brings challenges and risks to go along with its opportunities, and five leading examples include:
- Bias: Algorithmic bias is an issue that has already presented itself during the relatively brief existence of AI so far. Some systems, for example, have issued responses or generated content that could be classified as discriminatory or prejudiced, due to the training data they were given.
- Privacy: There are fears among populations and analysts about the amount of data being fed into AI systems and how such data could be misused, potentially violating people’s rights of privacy and falling foul of data privacy regulations, such as GDPR.
- Misuse: Like so many game-changing technologies, AI has the potential to be used for both benevolent and malicious purposes. It may be used to spread misinformation and “fake news,” influence public opinion, or even in cyber-attacks, for instance.
- Over-reliance: AI is so powerful, with the capacity to carry out tasks with remarkable precision and speed, that it will be tempting for organizations to integrate it into many of their workflows and decision-making processes. But AI cannot be treated as a substitute for human judgment.
- Sustainability: There are also fears about the energy costs associated with AI and the data centers needed to power it, plus the fact that some elements of the burgeoning AI industry may exploit workers in poorer nations worldwide.
Solving These Challenges: Regulation and Responsible Use of AI
With the right approach, it is possible to solve all the above challenges, and more, making AI the most valuable and beneficial new technology the world has seen since the advent of the internet. This will require a two-pronged strategy focusing on both regulation and responsible usage.
Europe is already leading the way in the first aspect. It has introduced the AI Act – a world-first regulatory framework related to artificial intelligence, laying out how it should be used to drive innovation without infringing on the fundamental rights of workers and the larger public.
Educational institutions like the OPIT – Open Institute of Technology are also leading the way in the second aspect, educating people around the world on how to work with AI in a responsible, ethical way, through programs like the MSc in Responsible Artificial Intelligence.
By establishing rules and regulations about AI’s usage and educating the tech leaders of tomorrow in how to work with AI in a fair and responsible way, the future is bright for this exciting and extraordinary new technology.
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