• Programs
    • Apply Now ➔
    Apply Now ➔
    The Magazine

    Masters in Machine Learning Online: The Top MSc Programs

    OPIT - Open Institute of Technology
    OPIT - Open Institute of Technology
    Jun 30, 2023 • 9 min read
    Share on:
    Share on Pinterest Share on LinkedIn

    Machines that can learn on their own have been a sci-fi dream for decades. Lately, that dream seems to be coming true thanks to advances in AI, machine learning, deep learning, and other cutting-edge technologies.

    

    Have you used Google’s search engine recently or admired the capabilities of ChatGPT? That means you’ve seen machine learning in action. Besides those renowned apps, the technology is widespread across many industries, so much so that machine learning experts are in increasingly high demand worldwide.
    

    

    Chances are there’s never been a better time to get involved in the IT industry than today. This is especially true if you enter the market as a machine learning specialist. Fortunately, getting proficient in this field no longer requires enlisting in a college – now you can finish a Master in machine learning online.
    

    

    Let’s look at the best online Masters in machine learning and data science that you can start from the comfort of your home.
    

    

    Top MSc Programs in Machine Learning Online
    

    

    Finding the best MSc machine learning online programs required us to apply certain strict criteria in the search process. The following is a list of programs that passed our research with flying colors. But first, here’s what we looked for in machine learning MSc courses.
    

    

    Our Criteria
    

    

    The criteria we applied include:
    

    

      

    • The quality and reputation of the institution providing the course
      • 

    • International degree recognition
      • 

    • Program structure and curriculum
      • 

    • Duration
      • 

    • Pricing
      • 

    

    Luckily, numerous world-class universities and organizations have a machine learning MSc online. Their degrees are accepted around the world, and their curricula count among the finest in the market. Take a look at our selection.
    

    


    Imperial College London – Machine Learning and Data Science
    

    

    The Machine Learning and Data Science postgraduate program from the Imperial College in London provides comprehensive courses on models applicable to real-life scenarios. The program features hands-on projects and lessons in deep learning, data processing, analytics, and machine learning ethics.
    

    

    The complete program is online-based and relies mostly on independent study. The curriculum consists of 13 modules. With a part-time commitment, this program will last for two years. The fee is the same for domestic and overseas students: £16,200
    

    

    European School of Data Science & Technology – MSc Artificial Intelligence and Machine Learning
    

    

    If you need a Master’s program that combines the best of AI and machine learning, the European School of Data Science & Technology has an excellent offer. The MSc Artificial Intelligence and Machine Learning program provides a sound foundation of the essential concepts in both disciplines.
    

    

    During the courses, you’ll examine the details of reinforcement learning, search algorithms, optimization, clustering, and more. You’ll also get the opportunity to work with machine learning in the R language environment.
    

    

    The program lasts for 18 months and is entirely online. Applicants must cover a registration fee of €1500 plus monthly fees of €490.
    

    

    European University Cyprus – Artificial Intelligence Master
    

    

    The European University in Cyprus is an award-winning institution that excels in student services and engagement, as well as online learning. The Artificial Intelligence Master program from this university treats artificial intelligence in a broader sense. However, machine learning is a considerable part of the curriculum, being taught alongside NLP, robotics, and big data.
    

    

    The official site of the European University Cyprus states the price for all computer science Master’s degrees at €8,460. However, it’s worth noting that there’s a program for financial support and scholarships. The duration of the program is 18 months, after which you’ll get an MSc in artificial intelligence.
    

    

    Udacity – Computer Vision Nanodegree
    

    

    Udacity has profiled itself as a leading learning platform. Its Nanodegree programs provide detailed knowledge on numerous subjects, such as this Computer Vision Nanodegree. The course isn’t a genuine MSc program, but it offers specialization for a specific field of machine learning that may serve for career advancement.
    

    

    This program includes lessons on the essentials of image processing and computer vision, deep learning, object tracking, and advanced computer vision applications. As with other Udacity courses, learners will enjoy support in real-time as well as career-specific services for professional development after finishing the course.
    

    

    This Nanodegree has a flexible schedule, allowing you to set a personalized learning pace. The course lasts for three months and has a fee of €944. Scholarship options are also available for this program, and there are no limitations in terms of applying for the course or starting the program.
    

    

    Lebanese American University – MS in Applied Artificial Intelligence
    

    

    Lebanese American University curates the MS in Applied Artificial Intelligence study program, led by experienced faculty members. The course is completely online and focuses on practical applications of AI programming, machine learning, data learning, and data science. During the program, learners will have the opportunity to try out AI solutions for real-life issues.
    

    

    This MS program has a duration of two years. During that time, you can take eight core courses and 10 elective courses, including subjects like Healthcare Analytics, Big Data Analytics, and AI for Biomedical Informatics.
    

    

    The price of this program is €6,961 per year. It’s worth noting that there’s a set application deadline and starting date for the course. The first upcoming application date is in July, with the program starting in September.
    

    

    Data Science Degrees: A Complementary Path
    

    

    Machine learning can be viewed as a subcategory of data science. While the former focuses on methods of supervised and unsupervised AI learning, the latter is a broad field of research. Data science deals with everything from programming languages to AI development and robotics.
    

    

    Naturally, there’s a considerable correlation between machine learning and data science. In fact, getting familiar with the principles of data science can be quite helpful when studying machine learning. That’s why we compiled a list of degree programs for data science that will complement your machine learning education perfectly.
    

    


    Top Online Data Science Degree Programs
    

    

    Purdue Global – Online Bachelor of Science Degree in Analytics
    

    

    Data analytics represents one of the essential facets of data science. The Online Bachelor of Science Degree in Analytics program is an excellent choice to get familiar with data science skills. To that end, the program may complement your machine learning knowledge or serve as a starting point for a more focused pursuit of data science.
    

    

    The curriculum includes nine different paths of professional specialization. Some of those concentrations include cloud computing, network administration, game development, and software development in various programming languages.
    

    

    Studying full-time, you should be able to complete the program within four years. Each course has a limited term of 10 weeks. The program in total requires 180 credits, and the price of one credit is $371 or its equivalent in euros.
    

    

    Berlin School of Business and Innovation – MSc Data Analytics
    

    

    MSc Data Analytics is a postgraduate program from the Berlin School of Business and Innovation (BSBI). As an MSc curriculum, the program is relatively complex and demanding, but will be more than worthwhile for anyone wanting to gain a firm grasp of data analytics.
    

    

    This is a traditional on-campus course that also has an online variant. The program focuses on data analysis and extraction and predictive modeling. While it could serve as a complementary degree to machine learning, it’s worth noting that this course may be the most useful for those pursuing a multidisciplinary approach.
    

    

    This MSc course lasts for 18 months. Pricing differs between EU and non-EU students, with the former paying €8,000 and the latter €12,600.
    

    

    Imperial College London – Machine Learning and Data Science
    

    

    It’s apparent from the very name that this Imperial College London program represents an ideal mix. Machine Learning and Data Science combines the two disciplines, providing a thorough insight into their fundamentals and applications.
    

    

    The two-year program is tailored for part-time learners. It consists of core modules like Programming for Data Science, Ethics in Data Science and Artificial Intelligence, Deep Learning, and Applicable Mathematics.
    

    

    This British-based program costs £16,200 yearly, both for domestic and overseas students. Some of the methods include lectures, tutorials, exercises, and reading materials.
    

    

    Thriving Career Opportunities With a Masters in Machine Learning Online
    

    

    Jobs in machine learning require proper education. The chances of becoming a professional in the field without mastering the subject are small – the industry needs experts.
    

    

    A Master’s degree in machine learning can open exciting and lucrative career paths. Some of the best careers in the field include:
    

    

      

    • Data scientist
      • 

    • Machine learning engineer
      • 

    • Business intelligence developer
      • 

    • NLP scientist
      • 

    • Software engineer
      • 

    • Machine learning designer
      • 

    • Computational linguist
      • 

    • Software developer
      • 

    

    These professions pay quite well across the EU market. The median annual salary for a machine learning specialist is about €70,000 in Germany, €68,000 in the Netherlands, €46,000 in France, and €36,000 in Italy.
    

    

    On the higher end, salaries in these countries can reach €98,000, €113,000, €72,000, and €65,000, respectively. To reach these more exclusive salaries, you’ll need to have a quality education in the field and a level of experience.
    

    

    Become Proficient in Machine Learning Skills
    

    

    Getting a Master’s degree in machine learning online is convenient, easily accessible, and represents a significant career milestone. With the pace at which the industry is growing today, it would be a wise choice.
    

    

    Since the best programs offer a thorough education, great references, and a chance for networking, there’s no reason not to check out the courses on offer. Ideally, getting the degree could mark the start of a successful career in machine learning.
    
                            
    Share this post:
    
Share on Pinterest
Share on LinkedIn
                                
    
                        
    
                    
    
                
    
            
    
            
    
                
      
                    
    • 
                        
      
                            
      
                                Search inside The Magazine
                            
      
                            
      
                                
      
                                    
                                
      
                                
                            
      
                        
      
                        
                    
      • 
                    
    • 
                        
      
                            From the same author
                        
      
                                                
                                
      
                                                                        
                                        
                                            
                                            
                                        
                                                                        
                                        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
                                    
                                
      
                                                
                        
                    
      • 
                    
    • 
                        
      
                            Categories
                        
      
                        
                    
      • 
                    
    • 
                        
      
                            Authors
                        
      
                        									
						
      
							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
                            
                        
    
                    
                    
                            
    
        
    
    
    

    


    
	
    
		
    
			
    
			
    
									
    
						Have questions?					
    
													
    
						
    Visit our FAQ page or get in touch with us!
    
					
    
								
    
											
    
							
    
								
							
    
							
    
																	
										WhatsApp									
																									
    
										Write us at +39 335 576 0263									
    
															
    
						
    
					
											
    
							
    
								
							
    
							
    
																	
										Email									
																									
    
										Get in touch at hello@opit.com									
    
															
    
						
    
					
											
    
							
    
								
							
    
							
    
																	
										Book a meeting									
																									
    
										Talk to one of our Study Advisors									
    
															
    
						
    
					
											
    
							
    
								
							
    
							
    
																	
    
										We are international									
    
																									
    
										We can speak in:									
    
																
      
									
    • 
										Spain
									
      • 
									
    • 
										Portugal
									
      • 
									
    • 
										Italy
									
      • 
									
    • 
										England
									
      • 
									
    • 
										USA
									
      • 
								
    
							
    
						
    
									
    
															
							Request info							
								
									
								
								
									
								
							
						
												
    
		
    
	
    

    


    


	
	
	


    





    


    
	
	
    
		
		
    
			
			
    
				
    
					
    
						
    
																				
    
						

    

     
      

      

      







      


      

      
					
      
				
      
			
      
		
      
	
      

      


      
	
	
      
		
		
      
			
			
      
				
      
					
      
						
      
																				
      
						

      

       
        

        

        







        


        

        
					
        
				
        
			
        
		
        
	
        

        


        
	
	
        
		
		
        
			
			
        
				
        
					
        
						
        
															
        
									Apply to OPIT