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    MSc in Computer Science: The Top Masters Courses & Programs

    OPIT - Open Institute of Technology
    OPIT - Open Institute of Technology
    Jul 1, 2023 • 9 min read
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    Finding an industry or even area of life that doesn’t utilize digital technologies is quite a challenge today. As computers continue to impact the ways we do business and live, understanding their capabilities and limitations becomes essential. This is the gist of what computer science is all about.

    The tasks of computer science keep growing in scope and complexity. This means the demand for professionals in the field is always on the rise. Global companies are always on the lookout not only for people who know computer science but are also experts in the field.

    For these reasons, getting an MSc in Computer Science can be the best career move in the modern landscape. Masters in Computer Science allows you to gain detailed knowledge and choose a specialized path. Better yet, holding such a degree elevates your chances of landing a well-paid job at a respectable organization.

    Getting an MSc Computer Science is undoubtedly a good idea. You can even do it online, with all of the conveniences of remote learning. Let’s look at the best Masters in Computer Science courses and find out what they offer in terms of professional development.

    Factors to Consider When Choosing an MSc Computer Science Program

    Picking the right course may be something of a challenge. Numerous institutions offer quality programs, so you might not know where to start or what to look for when making the decision. Here are the key factors that should influence your choice.

    Firstly, the reputation of the institution providing the course will matter greatly. Leading universities and learning organizations will offer the most comprehensive programs. Plus, their degrees will be accredited and recognized worldwide.

    Next, you’ll need to choose a particular curriculum and specialization that fit your needs and interests. Computer science is a broad field of study, so picking the right study path will be necessary.

    The institution you enroll in should have quality faculty members. This aspect is relatively straightforward: If you pick a reputable university, chances are the faculty will be up to par. On a similar note, such institutions will provide ample research opportunities.

    The financial aspect is, of course, another important factor. Tuition fees differ considerably between institutions, and some may provide considerable aid for upcoming students. Yet, that doesn’t mean you should opt for the most affordable variant – the combination of a reasonable price and quality education will be the winning one.

    When studying on-campus, the location and facilities will be crucial. While not the deciding factor, this may be a tipping point when comparing two otherwise evenly matched institutions.

    Lastly, career support is one of the most important advantages you can get from an MSc program. Some institutions provide considerable opportunities for career development, connecting students with leading companies in the field. Additionally, network-building options will matter in this regard.

    Top MSc Computer Science Courses and Programs

    Norwegian University of Science and Technology

    • Location: Gjøvik, Norway
    • Duration: Two years
    • Study Mode: Full-time
    • Requirements: Informatics bachelor’s or engineering degree; minimum average grade: C; minimum informatics credits: 80; documented informatics and mathematics knowledge
    • Tuition fees: No fees
    • Scholarships/Financial aid: Free program – no financial aid needed
    • Career prospects: Machine learning, gaming industry, AI, VR; possibility of Ph.D. program application

    Check out MSc in Computer Science at the Norwegian University of Science and Technology.

    KHT

    • Location: Stockholm, Sweden
    • Duration: Two years
    • Study Mode: Full-time
    • Requirements: Bachelor’s degree from a Swedish or another recognized university in informatics, computer science, or mathematics (minimum 180 ECTS credits); proficient use of the English language – IELTS 6.5, TOEFL 20, PTE 62, ESOL C1 (minimum 180 points)
    • Tuition fees: SEK 310,000; application fee is SEK 900
    • Scholarships/Financial aid: Scholarships are available from KTH, the Swedish Institute, and associated organizations; full and one-year scholarships available
    • Career prospects: Graduates from KHT have moved forward to Ph.D. studies worldwide or found jobs at leading tech companies like Google, Oracle, Saab, Spotify, and Bloomberg.

    Check out MSc in Computer Science at KHT.

    University Leiden

    • Location: Leiden, Netherlands
    • Duration: Two years
    • Study Mode: Full-time
    • Requirements: Bachelor’s degree in AI, Bioinformatics, Computer Science or a related program; English proficiency – IELTS 6.5, TOEFL 90
    • Tuition fees: Students from the EU, Suriname, or Switzerland: €2,314 yearly; other students: €19,600 yearly
    • Scholarships/Financial aid: Various scholarships available; EU students under the age of 30 are eligible for a Dutch government loan
    • Career prospects: Careers in AI, computer science and education, data science, and advanced computer systems

    Check out MSc in Computer Science at University Leiden.

    Specializations Within MSc Computer Science

    Computer science has numerous subcategories and fields of study. These fields are widely different, so you’ll need to choose your specialization carefully. Let’s look at the key disciplines of computer science that you can specialize in and what those disciplines mean.

    Artificial Intelligence and Machine Learning

    As a field of computer science, AI deals with methods and technologies that allow machines to simulate human intelligence. This includes machine learning, deep learning, and similar disciplines. Through learning methods, either assisted or unassisted by humans, machines can process data and draw conclusions somewhat independently.

    Data Science and Big Data Analysis

    Data science, as the name implies, deals with data gathering, processing, and analysis. This facet of computer science is particularly important, as it finds plenty of practical applications in business, other sciences, demographics, and statistics.

    A subset of data science, big data analysis focuses on extracting information from massive databases. A data scientist’s job is to compile the data and use advanced technological solutions to draw meaningful conclusions. The volumes of data analyzed this way far surpass anything that humans can achieve without computer assistance.

    Cybersecurity and Information Security

    Today, cybersecurity counts among the most important facets of computer science. Other disciplines gather, produce, and store copious amounts of data which often contain sensitive information. Unfortunately, modern criminals prey on that information to gain access to financial accounts, steal confidential data, and blackmail businesses and individuals.

    Cybersecurity attempts to foil attacks from malicious parties. As the methods of crime evolve, so do the technologies meant to fight them. From phishing prevention to protection from hacking, cybersecurity, and information security ensures sensitive data doesn’t end up in the wrong hands.

    Software Engineering and Development

    Software is at the core of all computer systems, and it’s an ever-evolving aspect of computer science. New software solutions are needed practically every day, and that’s where software engineering and development come in.

    Software engineers design new programs and work out how to implement them. Developers work on finding novel solutions to practical and theoretical challenges. These two branches of computer science are responsible for helping machines keep up with users’ demands, both privately and professionally.

    Human-Computer Interaction and User Experience Design

    We might not think much about the way we interact with computers. At least that’s the case if the user experience is done right. Designing the elements that people use in regular interaction reflects how efficiently computer systems work. Without quality user experience or means of interaction, software alone doesn’t serve much purpose.

    Networking and Cloud Computing

    A standalone computer system is a rarity these days. Networking, the internet, and cloud computing unlocked the full potential of the digital world. Today, computers can do their best when connected online, which is why these aspects of computer science count among the most important today.

    Internet of Things and Embedded Systems

    The Internet of Things (IoT) refers to a network of interconnected smart devices. This technology makes smart homes possible, but that’s only a small part of what IoT can do. Automated manufacturing, logistics, and numerous other complex systems function on this principle. In a sense, IoT and embedded systems represent the pinnacle of computer science since it brings together all other fields of research.

    Tips for a Successful MSc Computer Science Application

    Applying for an MSc in Computer Science is a step that shouldn’t be taken lightly. Your application will require careful consideration, particularly regarding the career path you wish to take. It would be best to start with a list of programs that fit your chosen field of research.

    Once you have that list, you should narrow the choice according to the specific criteria that we listed here. To recap, those criteria are:

    • The institution’s reputation and accreditation
    • The curriculum
    • Faculty and opportunities for research
    • Fees and scholarships/financial aid
    • Location and facilities
    • Networking opportunities and career support

    After you choose the program, it will be time to prepare the strongest application possible. You’ll have the best chances of getting accepted into the program with a well-written statement of purpose, the appropriate letters of recommendation, test scores and academic transcripts, and written proof of extracurricular activities and work experience.

    Lastly, you should prepare to visit the campus and schedule an interview. Don’t disregard this aspect of the application process, as it could easily determine whether you’ll get accepted.

    Start Your Computer Science Master’s Journey Today

    Getting an MSc in Computer Science may be a significant boost for your career. Select the right program, and you might find yourself at the top of the job market. If your interests fall into any field of computer science, consider enrolling in a master’s program at a leading institution – it will be an excellent career move.

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      Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
      OPIT - Open Institute of Technology
      OPIT - Open Institute of Technology
      April 14, 2025

      Source:

      Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

      By Gianni Rusconi

      Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

      The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

      CEOs and AI

      When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

      In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

      Read the full article below (in Italian):

      Read the article
      The Lucky Future: How AI Aims to Change Everything
      OPIT - Open Institute of Technology
      OPIT - Open Institute of Technology
      April 10, 2025

      There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

      But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

      That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

      However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

      How AI Aims to Change Everything

      For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

      From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

      While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

      • Where we are currently with AI and future trajectories
      • The impact AI is having on the job landscape
      • Sustainability concerns and ethical dilemmas
      • The fundamental risks associated with current AI technology

      According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

      Industry Applications of AI

      While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

      That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

      This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

      We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

      The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

      This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

      The AI Revolution and the Job Market

      According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

      To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

      However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

      Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

      Is AI Sustainable?

      While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

      Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

      To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

      Risks of Using Generative AI

      While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

      • Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
      • Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
      • Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
      • Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
      • Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
      • Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

      Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

      The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

      OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

      A Lucky Future

      Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

      Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

      Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

      It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.

      Read the article
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      Francesco Profumo
      Francesco Profumo
      Avatar
      John Loewen
      Professor @OPIT, PhD in Computer Science, Former Professor @Chulalongkorn University and @Vancouver Island University. Location: Italy Teaches Computer Architectures (BSc).
      Karim Bouzoubaa
      Karim Bouzoubaa
      Professor @ OPIT, Professor of Data Science & AI @ Mohammed V University in Rabat, PhD @ Laval University. Location: Canada, Morocco. Teaches Programming courses (BSc).
      Avatar
      Khaled Elbehiery
      Professor @ OPIT, Senior Director & Network Engineer @ Charter Communications, Professor @ DeVry University and @ Park University. Location: USA. Teaches: Computer Networks (BSc).
      Lokesh Vij
      Lokesh Vij
      Professor @ OPIT, Software Engineer @ Symantec, Faculty @ Seneca College. Location: Canada. Teaches Cloud Computing courses (BSc), Big Data and Cloud Computing Infrastructure (MSc).
      Go to all authors

    Related posts

    Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
    OPIT - Open Institute of Technology
    OPIT - Open Institute of Technology
    Apr 14, 2025 • 6 min read

    Source:

    Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

    By Gianni Rusconi

    Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

    The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

    CEOs and AI

    When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

    In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

    Read the full article below (in Italian):

    Read the article
    The Lucky Future: How AI Aims to Change Everything
    OPIT - Open Institute of Technology
    OPIT - Open Institute of Technology
    Apr 10, 2025 • 7 min read

    There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

    But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

    That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

    However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

    How AI Aims to Change Everything

    For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

    From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

    While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

    • Where we are currently with AI and future trajectories
    • The impact AI is having on the job landscape
    • Sustainability concerns and ethical dilemmas
    • The fundamental risks associated with current AI technology

    According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

    Industry Applications of AI

    While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

    That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

    This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

    We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

    The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

    This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

    The AI Revolution and the Job Market

    According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

    To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

    However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

    Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

    Is AI Sustainable?

    While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

    Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

    To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

    Risks of Using Generative AI

    While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

    • Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
    • Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
    • Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
    • Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
    • Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
    • Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

    Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

    The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

    OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

    A Lucky Future

    Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

    Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

    Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

    It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.

    Read the article

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