Online Master’s in Computer Science: The Top Leading Programs

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Jul 2, 2023 • 9 min read

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You’d be hard-pressed to find a more rapidly evolving industry than computer science today. It seems like new solutions and applications in the field pop up every day, and the market has never been hungrier for talent.

If you’re interested in computer science, you’re in luck. This industry has some of the best-paid jobs worldwide and is full of exciting developments and novel challenges. Of course, many people are competing for those work positions, which is why you must do everything in your power to gain an advantage.

With an online masters computer science program, you can get the edge over other candidates in the market. Completing such a program will provide you with cutting-edge knowledge and equip you with the most relevant skills. In other words, an online MSc computer science program may help you start a career in the field.

But choosing the best online masters computer science program may be more complex than it seems. Numerous institutions offer this type of education, so finding the top options among the crowd could be a challenge.

This article will serve as your complete guide to online masters computer science programs. We’ll explain what to look for, recommend some of the leading options, tell you how to apply, and outline what awaits once you graduate.

Factors to Consider When Choosing an Online Masters in Computer Science Program

It goes without saying that you shouldn’t enroll in a master’s program without closely examining your options. Be sure to pay attention to specific criteria when considering where you’ll get your online MSc computer science degree:

Accreditation: You’ll want to graduate at an accredited institution with degrees that are recognized worldwide. Other universities and employers won’t consider unaccredited degrees particularly valuable or trustworthy. Plus, accreditation serves as proof that an educational institution meets certain international standards.
Curriculum and specializations: Your choice of an online masters computer science program will depend on the classes provided. The curriculum should be appropriate for your purposes and goals. And since computer science is a broad field, you’ll want to ensure the program has the right specialization options for you.
Faculty expertise: A master’s program will often be only as efficient as the people teaching it. Faculty members at your program of choice should, of course, be experts. They should also have extensive experience to provide practical guidance and show you how computer science is applied in real-life.
Program format and flexibility: Online programs have the major advantage of not requiring you to physically attend classes. This means that a certain level of flexibility is expected, both in terms of day-to-day lectures and deadlines. The flexibility principle often extends to the curriculum itself, with many programs offering a large number of electives.
Tuition fees and financial aid: Considering the tuition price is always worthwhile. Like everything else in the market, master’s programs can be under- or overpriced. You should take care that you’re getting the right value for a reasonable sum. Plus, there are usually financial aid options available to help soften the financial impact.
Student support services: Lastly, the best online masters computer science programs will offer extensive support to students. This can represent a massive benefit when you need counseling or extra guidance. Even better, your program might include career support, nurturing you from student to graduate to employee.

Top Online Masters in Computer Science Programs

1. International University of Applied Sciences (IU) – Master’s in Computer Science

This program offers practical education in computer science. Focusing mostly on artificial intelligence, cybersecurity, and data science, it lasts between two and four years, depending on whether you study full or part-time.

Key Features:

Dual degree option available
Accredited according to European standards
Entirely flexible

To enter this program, you’ll need to provide a computer science-focused undergraduate degree from a recognized institution. English proficiency will also be mandatory. The monthly tuition fee is €278 for full-time, €209 for part-time (three years), and €165 for part-time (four years) students.

2. University of Essex – MSc Computer Science

This two-year program by the University of Essex starts by examining the theoretical fundamentals. Then, it allows you to choose a specific field of focus and study it in detail through lectures and practical applications.

Key Features:

BCS accreditation
Tuition fee covers learning tools like programming languages
Suitable for students from a different background

You can apply for this program with an undergraduate degree or if you’ve worked in a relevant field for a minimum of three years. English language qualification is acceptable from IELTS or a similar school. If lacking such qualifications, the University of Essex also lets you take a free online test. The tuition fees are £12,167 for UK and £12,428 for international students with possibilities of scholarships and discounts.

3. MIA Digital University – Master in Computer Science – Cybersecurity, Data Analytics, and Artificial Intelligence

Based in Barcelona, Spain, the MIA Digital University offers a computer science program that tackles some of the most requested profiles in the industry. You’ll learn about the latest developments in cybersecurity, data analytics, and AI, as well as how to apply them in practice. The program lasts for one year.

Key Features:

Dual degree with Universidad a Distancia de Madrid (Udima)
Student internships offered
Heavily project-based

Application for this program will require a previous degree, which doesn’t have to be from the computer science field. You’ll also need to submit a resume or CV and a valid ID. The price of the program is €3,900, with scholarships available.

4. BTH Sweden – Master’s Program in Software Engineering

Somewhat more specific than other programs on the list, this MSc focuses on software engineering. However, the program also leans heavily into data science, machine learning, and AI. For that reason, you may view it as a computer science program with an emphasis on software engineering. The program is two years long.

Key Features:

Mixed-time structure
Work in groups and individually
Based on leading software engineering research

To apply for this program, you’ll need a BSc degree in Engineering with a minimum 15-credit degree project. Professional experience of no less than two years in software development is also required, preferably with programming involved. The program doesn’t have a tuition fee for UK students, while others will need to pay SEK 60,000 for each semester.

How to Apply for an Online Masters in Computer Science Program

Precisely how you apply for an online masters computer science program will depend on the institution. There’s no universal application process, but you can keep certain guidelines in mind.

First, get detailed information about the requirements. Most master’s programs will require previous education in the field, although some may accept provable work experience instead of a degree.

Certain programs will also ask for a letter of recommendation and statement of purpose. But even if these documents aren’t requested, including them in your application will usually be a plus. Also, online MSc computer science programs are commonly held in English, so you’ll need a level of language proficiency and the appropriate certification.

Learning all of the relevant information in time and getting your documents in order will be pivotal. The last thing you’d want to do is miss out on a program by submitting an incomplete application. Additionally, you’ll have the greatest chances of success if you apply for a program with requirements you’re certain you’ll meet.

Every program will have specified deadlines and dates for application, interviews, covering the fees, and enrollment. Naturally, missing those dates would likely result in you not being accepted, so do your best to stay on track.

Career Prospects for Graduates of Online Masters in Computer Science Programs

Computer science graduates have plenty of options in the job market. Experts in this field are needed in various industries, including finance, IT, healthcare, and commerce.

Depending on your specialization, you could work in programming, database management, cybersecurity, robotics, network engineering, etc. The average base yearly salary for a computer science MSc graduate is €56,000. Of course, this will vary widely depending on your field of expertise, industry, and experience.

Your online masters computer science degree will also allow you to continue your education. You can move forward to different specializations, either in a particular field or interdisciplinary. In addition, an MSc may make you eligible for a PhD program, if you’re interested in further academic progress.

Complete an Online MSc Computer Science Program and Start a Rewarding Career

Choosing an online MSc computer science program that fits your goals can be an immensely valuable career and educational move. This degree will give you an advantage in the job market and help you hone your professional skills. Plus, enrolling in a postgraduate program will create networking opportunities that may be of great importance.

If getting an MSc in computer science sounds enticing, there’s no reason not to start working on it right now. Research the programs that suit your needs and don’t hesitate to apply. You’ll be making a worthwhile step in the right direction.

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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

April 14, 2025
Source:
- Il Sole 24 Ore, published on April 14th, 2025
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.

“CEOs who already work with AI – explains the OPIT expert – see the investment in compliance as necessary, the latter as an opportunity: and the latter, on paper, have the advantage of being able to define a strategy also in terms of ethics and civil responsibility”

SMEs in greater difficulty

There is a further theme that accompanies the diffusion of AI in the European corporate fabric and that is the difference in “approach” between large companies and SMEs. The top executives of enterprise-class organizations, as Casale confirms, have budgets and resources to adequately address and manage the challenge of compliance. Small and medium-sized businesses, on the other hand, are in a waiting position to understand how to carry forward the development process and the risk that many may slow down in the innovation path, and that a conservative attitude towards the use of artificial intelligence prevails, is clear.

Lastly, no less important is the issue of skills, which is very much felt in both the technical and legal fields. “The skills and requirements of AI Engineers and Data Scientists, with all their variations on the theme, are now defined and it is clear – Casale assures – that there is a strong increase in demand. However, I am of the opinion that there cannot be training that is only engineering-based or focused solely on regulatory aspects: instead, we need paths that combine the two dimensions and that lead to preparing the new Chief AI Officers, that is, high-level responsibility figures called to govern all activities related to the use of artificial intelligence”. Nonetheless, according to the expert, we need a layer of specialists who study the impacts and implications of technology on society, anticipating possible risks.

Old universities are not enough

In conclusion, it remains to be asked whether Italy is up to speed in meeting this need, and in this regard Casale’s answer is once again precise and transparent: “Old-style universities can no longer be functional for this purpose, because we need to understand how to teach a new mindset and not a technology as such, given the speed of its evolution. We are in the midst of a phase of great change and evolution towards dynamic study paths, and in other European countries this transformation has already begun”. In the meantime, artificial intelligence continues on its course and suggests that it will not be a passing fad. On the contrary. “AI – concludes the OPIT professor – exists and is here to remain a protagonist: to teach it and bring it to the ground in an adequate way, correct governance of the technology is necessary and the AI Act is an important first step in this direction. But there is still a lot of work to do”.

Read the full article below (in Italian):
- Il Sole 24 Ore
Check out OPIT degrees

BSc in Digital Business MSc in Digital Business and Innovation MSc in Responsible Artificial Intelligence MSc in Applied Data Science and AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI
- Career aligned
- Fully Online
- EU-accredited institution
Read the article
The Lucky Future: How AI Aims to Change Everything
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.
Check out OPIT degrees

MSc in Digital Business and Innovation MSc in Responsible Artificial Intelligence MSc in Applied Data Science and AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI MSc in Data Science & AI
- Career aligned
- Fully Online
- EU-accredited institution
Read the article
Categories
Authors

Francesco Profumo

John Loewen

Professor @OPIT, PhD in Computer Science, Former Professor @Chulalongkorn University and @Vancouver Island University. Location: Italy Teaches Computer Architectures (BSc).

Karim Bouzoubaa

Professor @ OPIT, Professor of Data Science & AI @ Mohammed V University in Rabat, PhD @ Laval University. Location: Canada, Morocco. Teaches Programming courses (BSc).

Khaled Elbehiery

Professor @ OPIT, Senior Director & Network Engineer @ Charter Communications, Professor @ DeVry University and @ Park University. Location: USA. Teaches: Computer Networks (BSc).

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

Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management

OPIT - Open Institute of Technology

Apr 14, 2025 • 6 min read

Source:

Il Sole 24 Ore, published on April 14th, 2025

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.

“CEOs who already work with AI – explains the OPIT expert – see the investment in compliance as necessary, the latter as an opportunity: and the latter, on paper, have the advantage of being able to define a strategy also in terms of ethics and civil responsibility”

SMEs in greater difficulty

There is a further theme that accompanies the diffusion of AI in the European corporate fabric and that is the difference in “approach” between large companies and SMEs. The top executives of enterprise-class organizations, as Casale confirms, have budgets and resources to adequately address and manage the challenge of compliance. Small and medium-sized businesses, on the other hand, are in a waiting position to understand how to carry forward the development process and the risk that many may slow down in the innovation path, and that a conservative attitude towards the use of artificial intelligence prevails, is clear.

Lastly, no less important is the issue of skills, which is very much felt in both the technical and legal fields. “The skills and requirements of AI Engineers and Data Scientists, with all their variations on the theme, are now defined and it is clear – Casale assures – that there is a strong increase in demand. However, I am of the opinion that there cannot be training that is only engineering-based or focused solely on regulatory aspects: instead, we need paths that combine the two dimensions and that lead to preparing the new Chief AI Officers, that is, high-level responsibility figures called to govern all activities related to the use of artificial intelligence”. Nonetheless, according to the expert, we need a layer of specialists who study the impacts and implications of technology on society, anticipating possible risks.

Old universities are not enough

In conclusion, it remains to be asked whether Italy is up to speed in meeting this need, and in this regard Casale’s answer is once again precise and transparent: “Old-style universities can no longer be functional for this purpose, because we need to understand how to teach a new mindset and not a technology as such, given the speed of its evolution. We are in the midst of a phase of great change and evolution towards dynamic study paths, and in other European countries this transformation has already begun”. In the meantime, artificial intelligence continues on its course and suggests that it will not be a passing fad. On the contrary. “AI – concludes the OPIT professor – exists and is here to remain a protagonist: to teach it and bring it to the ground in an adequate way, correct governance of the technology is necessary and the AI Act is an important first step in this direction. But there is still a lot of work to do”.

Read the full article below (in Italian):

Il Sole 24 Ore

Read the article

The Lucky Future: How AI Aims to Change Everything

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.