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\u201cMachines will dominate the world only if we humans allow it \u2013 if we train them to break the rules,\u201d says Ioannis Emiris, president of the board of directors and director general of the Athena Research Center. As the only research center in Greece specializing in digital sciences and technologies, Athena plays a pivotal role in the country\u2019s leap toward artificial intelligence (AI).<\/p>\n
\u201cMachines,\u201d he explains during a quiet lunch in the northern suburb of Kifissia, not far from his base, \u201care indeed becoming smarter than us; they can solve problems they have never encountered before. However, it is by no means inevitable that they will turn against humanity if we implement proper safeguards.\u201d<\/p>\n
Artificial intelligence, he notes, is evolving uncontrollably \u2013 and rapidly. \u201cHowever, it will become more specialized across fields. Interest in AI will eventually cool down, and it will become commonplace \u2013 ubiquitous, essential, but ordinary.\u201d Emiris speaks with simplicity and calm authority, easing the anxieties of the uninformed. He exudes the composure of someone who has introduced generations of students in the USA, Japan, France, Switzerland and Greece to the complex world of artificial neural networks. His contributions include groundbreaking work in computational geometry, algorithms that solve mathematical problems quickly, and cutting-edge research into 3D artificial intelligence.<\/p>\n
When pressed about fears surrounding AI, Emiris addresses the challenges of bias. Algorithms, he explains, are trained using data that may reflect societal prejudices or flawed human attitudes, which can lead to harmful decisions. Can we create algorithms free from such issues?<\/p>\n
\u201cWe can,\u201d he affirms. \u201cI am currently coordinating a European project called AutoFair, which focuses specifically on this: developing methods for automated machine learning to ensure greater fairness in decision-making systems. Of course, this is highly complex, because it\u2019s not enough to simply hide attributes like gender, ethnicity, or income. You need an algorithmic solution from the outset \u2013 that is, you must create better algorithms by addressing foundational scientific and research questions. To achieve fair AI, we need strong basic research. Without it, AI risks exacerbating inequality and limiting access.\u201d<\/p>\n
He continues: \u201cBasic research also provides a competitive edge. For instance, it\u2019s what made Google the powerhouse it is today. Stanford PhD students developed an algorithm in a course under the mentorship of Indian professor Rajeev Motwani, a pioneer in randomized algorithms. Do you know his story?\u201d he asks.<\/p>\n
When I admit I don\u2019t, he recounts: \u201cMotwani, who was also my professor at Stanford, became a shareholder in Google thanks to his mentorship. He amassed great wealth, built a swimming pool at his home, but tragically, he didn\u2019t know how to swim and drowned. He was only 47.\u201d<\/p>\n
What shaped Emiris personally? \u201cMy family and my studies in the US. The surname Emiris originates from the island of Kasos. My grandfather\u2019s family, who had emigrated to Alexandria, carried the diasporic spirit in their DNA. My father, who grew up in Egypt and studied engineering in France \u2013 he saw a mountain for the first time at 20 in Grenoble and in Greece at 25 \u2013 wanted me to pursue my education in the US. So, as soon as I finished high school, I left for Princeton.\u201d<\/p>\n
There, he earned his first degree in computer science, followed by a master\u2019s and a PhD at Berkeley, before returning to Europe \u2013 specifically France. \u201cWhy?\u201d I ask.<\/p>\n
\u201cWe were a Francophile family, and I also wanted to return to Europe. I had idealized it as a place of student life, social engagement, and politics. Life at American universities is intense, heavily focused on time management, even if it retains a certain sense of innocence. So, I found myself in the South of France, in a society that was closed, traditional, and politically conservative, much like Greek culture. Of course, the region itself was exceptional, and the work environment at INRIA Sophia Antipolis \u2013 known as the French Silicon Valley on the Cote d\u2019Azur \u2013 was remarkable.\u201d<\/p>\n
After that came his tenure at the National Technical University of Athens (NTUA) in the Department of Informatics and Telecommunications, along with his leadership role at Athena. The list of the center\u2019s success stories is long. What are the most notable?<\/p>\n
\u201cThe acquisition of the spinoff Innoetics by Samsung,\u201d Emiris begins. \u201cThe pioneering use of open data, particularly in sensitive medical applications, which is a European first. The clusters and incubators of Corallia, which have supported over 800 innovation companies and startups. Some of these companies, like Helic and Inaccess, have soared to success, eventually being acquired by major US tech firms like Ansys and Power Factors. Today, Corallia is also supporting 20 space technology companies.<\/p>\n
\u201cAnother success story is Meltemi, the Greek equivalent of ChatGPT. It\u2019s in high demand. However, ChatGPT in general must be specialized to achieve over 90% accuracy in critical fields such as justice, healthcare, public administration, education, and industry. It also needs to become more transparent and reliable.\u201d<\/p>\n
Emiris highlights the transformative changes at Athena, particularly with the establishment of the Archimedes AI unit. Archimedes focuses on artificial intelligence, data science, and algorithms and was founded with the support of the prime minister and the Greece 2021 Committee. Its creation involved significant contributions from luminaries like Constantinos Daskalakis, Christos H. Papadimitriou, and Timos Sellis. Another milestone was the founding of HERON, the first Robotics Center of Excellence (CoE), which is dedicated to transferring research results into the economy.<\/p>\n
Your most dynamic spinoff? \u201cAviSense.ai. It\u2019s powered by researchers from Athena and the University of Patras. The company focuses on autonomous driving technology, developing vehicles capable of \u2018seeing\u2019 behind physical obstacles, offering multiple communication channels, and planning the safest possible routes using diverse types of visual information.\u201d<\/p>\n
Have you built robots? \u201cYes. One of our robots operates in vineyards, monitoring plants for diseases. It doesn\u2019t resemble a humanoid \u2013 it looks more like a spider. It\u2019s also designed to harvest the fruit. Another robot cleans ship cargo holds, meticulously removing pollutants from compartment walls. For example, after coal has been transported, the robot ensures the space is clean enough to carry wheat. Robots are invaluable for challenging tasks. They can enter fires, descend into wells or oil tanks filled with fumes, and even perform missions in space \u2013 the ultimate frontier for innovation.\u201d<\/p>\n
What does a good algorithm require? \u201cComputational resources. A strong research paper \u2013 the kind that gets accepted at a top-tier international conference \u2013 costs around \u20ac10,000 to produce. A PhD student needs at least three such papers to complete their doctorate. To conduct experiments and train machines, vast amounts of data are necessary. Machines learn from examples, which are expensive, often insufficient, and require significant preprocessing to become useful.<\/p>\n
\u201cWe need open data, open science, and open-minded research. This year, the Nobel Prizes in Physics and Chemistry were awarded entirely to experts in artificial intelligence: one for using physics tools in designing artificial neural networks, and the other for computational protein design. This not only underscores the dominance of AI technology in our lives but also highlights that science, at its core, is universal and interconnected,\u201d says Emiris, who trains exceptionally skilled students \u2013 some of whom launch companies while still in their fourth year of studies.<\/p>\n
\u201cThey use it as part of their research. A paper written entirely by ChatGPT won\u2019t be good \u2013 it lacks originality and proper citations. If you ask a student to identify and document the sources ChatGPT used, they\u2019ll end up doing the work they should have done from the start.<\/p>\n
\u201cThat said, the new version, ChatGPT 4.0, is impressive. It\u2019s more accurate and up-to-date, combining older texts with new online references. But the overall question remains: Who controls these systems? Through a tool you believe is objective, someone could spread fabricated information. We need to educate society about how machines think and the risks they pose.\u201d<\/p>\n
\u201cArtificial intelligence consumes immense energy resources. Recently, we learned that Unit 1 of the Three Mile Island Nuclear Station in Pennsylvania, which shut down in 2019 (Unit 2, as you might recall, was the site of the most serious nuclear accident in US history in 1979), is being reopened to meet Microsoft\u2019s growing energy demands for AI. Nuclear energy is being revived to power machine learning systems.<\/p>\n
\u201cHowever, it\u2019s critical that we focus on green artificial intelligence: algorithms that consume less energy, systems that train more efficiently, and intelligent machines that learn with less data. These systems are already capable of generating text, creating images, mimicking voices like Putin\u2019s, producing films, and will soon play a pivotal role in developing medicines.<\/p>\n
\u201cAI must be sustainable, transparent, and socially inclusive. This is a monumental challenge \u2013 and a legacy we must leave for the next generation. Overall, I\u2019m optimistic. Greece has extraordinary potential and can achieve much more than it has so far.\u201d\u00a0<\/p>\n<\/p><\/div>\n