>> opinions

του Τέλη Τύμπα, Καθηγητής Ιστορίας της Τεχνολογίας, ΕΚΠΑ

Η ιδεολογία απόδοσης νοημοσύνης σε υλικές διατάξεις, αυτό που σήμερα αποκαλούμε «Τεχνητή Νοημοσύνη» (ΤΝ), δεν υπάρχει στις κοινωνίες της αρχαιότητας και των μέσων χρόνων. Είναι μια ιδεολογία που προκύπτει μαζί με τις κοινωνίες των νεότερων χρόνων, συμβάλλοντας με καθοριστικό τρόπο στη διαμόρφωσή τους. Για τον Σωκράτη, τον Πλάτωνα και τον Αριστοτέλη, όπως και για κάθε επιφανή θεολόγο του Βυζαντίου, η αναφορά σε «τεχνητή νοημοσύνη», η αναφορά σε ενδεχόμενο κατασκευής κάποιας «τεχνητής νοημοσύνης", δεν θα έβγαζε κανένα νόημα. Οι υλικές διατάξεις της αρχαιότητας και των μέσων χρόνων ήταν εργαλεία (και απλοί, σχετικά, μηχανισμοί) αλλά όχι μηχανές, δηλαδή υλικότητες όπως το σφυρί και το δρεπάνι, οι οποίες δεν έχουν ένα ορατό εξωτερικό και ένα αθέατο εσωτερικό. Δεν είναι δηλαδή «μαύρα κουτιά», όπως οι μηχανές της νεωτερικότητας, με ένα αθέατο-αδιαφανές εσωτερικό, όπου θα μπορούσε να κρύβεται κάποια τεχνητή νοημοσύνη. Το σφυρί και το δρεπάνι δεν έχουν κάτι μέσα τους που δεν βλέπουμε, σε αντίθεση με την ατμομηχανή, την ηλεκτρογεννήτρια και τον ηλεκτρονικό υπολογιστή. 

Αυτό εξηγεί γιατί η ιδεολογία περί τεχνητής νοημοσύνης εμφανίζεται παράλληλα με τις απαρχές τις ιστορικής περιόδου που αντιστοιχεί στον καπιταλισμό. 

Του Δρ. Ηρακλή Βογιατζή

Την τελευταία πενταετία η Τεχνητή Νοημοσύνη (ΤΝ) έχει αποκτήσει μυθικά χαρακτηριστικά. Ο διάλογος στην δημόσια σφαίρα αποδίδει στη νέα τεχνολογία εξωπραγματικές ιδιότητες και ασχολείται με τις «υπαρξιακές απειλές» που την συνοδεύουν. Μερικά ερωτήματα που απασχολούν τον τύπο και τον κοινωνικό διάλογο στοχάζονται τις μελλοντικές επιδράσεις της ΤΝ:

Θα εκτοπίσει τον άνθρωπο από την παραγωγή; Ήρθε το τέλος της εργασίας; Κινδυνεύει να αφανίσει την ανθρωπότητα με τη συνείδηση που αποκτά; Γίνεται αυτόνομη και μπορεί πλέον να αναπαράγει τον εαυτό της;

By Stavros Orfeas Zormpalas

We need not imagine science-fiction (or near-future) scenarios with fully autonomous, embodied, or super-intelligent artificial agents in order for pressing ethical questions to arise. Current AI systems make decisions with moral consequences (where a self-driving car should swerve during an accident, which job candidates are worth shortlisting, and which inmates should be granted parole). People are increasingly using Large Language Models (e.g. Therapist GPT) to seek counsel, life advice, and even therapy.

Even less obviously problematic cases are still ones where value judgments (judgments about what is good or bad, right or wrong, worth pursuing or worth avoiding)  lurk in the background. Consider the case where one visits a new city and asks ChatGPT to tell them what is worth seeing in a three-day trip. While the LLM is not making a moral judgment per se, its judgment has a tangible, albeit minor, impact on the person’s well-being. For the LLM to succeed in making the judgment, its verdicts needed to, at some level, become aligned with the user’s human preferences. An AI that is involved directly or indirectly in decision-making (either by deciding for us, or by being consulted for one of our decisions) enters the domain of the practical, and thereby, the moral: it, in some sense, decides or helps decide what is worth doing.

by Konstantinos Sioumalas-Christodoulou 

AI’s incursion into the private sector is often framed as a sudden rupture. Yet, AI is better understood as the latest surge within a decades-long information and communications technology (ICT) revolution, one that has been mechanising mental rather than manual work (Perez, 2024). 

This historical framing matters: it reminds us that the real question is not whether AI will transform business, but who will benefit, under what institutional arrangements, and with what distributional consequences.

by Andromachi Vasilikopoulou

Disruptive innovation is always a great challenge for legislation. The "pacing problem" (Marchant et al., 2011), the fact that technology and law develop at uneven paces, reaches its ultimate point here, since AI develops exponentially. Still, social, economic, and legal systems change incrementally. The expression "law lag", found in the literature, vividly describes the laborious process of law keeping pace with the rapid progress of technology. The gap between AI technologies and legislation sometimes leads to the perception that traditional legislation cannot tackle this new challenge (Cerca et al., 2015) or that regulating AI is impossible. Thus, the notorious Collingridge dilemma for the social control of technology escalates drastically regarding AI.

The complex and opaque networks that have developed in the AI industry pose even greater difficulty in handling this problem. Furthermore, AI, which is established as a general-purpose technology, broadens and escalates the above problem, as it aims to cover undefinable fields and can be used in unpredictable ways with unforeseen social impacts. Moreover, it interferes with human experience and decision-making processes, affecting our cognitive function and awareness of its consequences.  

How, then, could our conventional legal system solve an equation with so many unknowns?

by Elli Danae Vartziotis

The introduction of Artificial Intelligence (AI) into environmental and sustainability fields is often presented as an inevitable technological solution to the climate crisis. Indeed, AI already plays a key role in several environmental applications; it supports extreme-weather prediction, renewable-energy forecasting, wildlife monitoring, and biodiversity assessment (Vinuesa et al., 2020). These examples show that AI can provide genuine operational value in specific domains. 

However, many of the more ambitious sustainability applications, such as improving energy grids, making infrastructure climate-resilient, or reducing industrial emissions with AI, remain largely at the research or pilot stage, with limited evidence of widespread deployment (Johnson et al., 2025; Rohde et al., 2024). Even where AI tools are deployed, they typically address well-defined tasks rather than delivering the broad, systemic transformations often invoked in public narratives. Distinguishing between established applications and those that remain emergent or speculative is therefore essential for understanding AI’s real contribution to environmental and sustainability goals.

by Kornilia Papanastasiou

The drive for automation increasingly shapes every aspect of contemporary life, with technological artefacts and infrastructures structuring our actions, behaviours, and interactions. Artificial Intelligence (AI), in particular, has become a central technology; AI is involved deeply in everything from healthcare access to hiring decisions, criminal sentencing, and everyday communication. Rather than viewing technology through a deterministic lens - as neutral, autonomous, and detached from social interests - recent scholarship highlights a model of co-shaping: society shapes technology while technology, simultaneously, reshapes society. 

Gender stands in a mutually constitutive relationship with technology. Engendered ideologies become embedded in the design, production and use of technologies; this, in turn, reinforces cultural norms, values, and expectations about gender. Indicatively, feminist scholars caution against what D’Ignazio and Klein (2020) conceptualise as “Big Dick Data” —a term describing grand data-driven projects built on masculine fantasies of objectivity, scale, and control, while ignoring context, culture, and lived experience.

by Vasilis Argentinis

As artificial intelligence systems increasingly mediate access to resources, shape public discourse, and automate decision-making, the protection and expansion of human rights must be central to their development and deployment. 

We affirm that AI must serve people, not power.

by Christos Koutsospyros

Automated decision-making in public administration is gaining increasing ground, radically transforming bureaucratic procedures and the state apparatus itself. The processes most suitable for automation are routine administrative tasks, such as the recording, registration, preparation, classification, and verification of the accuracy of information received by public authorities.

The use of Artificial Intelligence systems and algorithms promises the simplification of bureaucratic procedures, allowing public servants more time to focus on tasks that require human judgment, creativity, and discretion.

By Giorgos Bouritsas & Yannis Panagakis

Artificial intelligence (AI) is no longer something distant or futuristic. It has become embedded in everyday life: on our phones, in the services we use, in public administration, and in decisions about work and benefits. Many choices that affect us are now mediated by systems we never see.

Yet, most people do not understand how these systems work or whether they treat us fairly. This is not merely a technical issue. It is a question that touches our dignity, our rights, and the quality of our democracy.