In 150 words at most, please write me a professional, eloquent and gramatically impressive conclusion for the following question: “In your opinion, should students have unlimited access to these AI systems (e.g., Chat GPT, Claude 2, Bard etc.)? Please draw on personal examples as well as academic references to support your answer.” Given that this is the answer I’ve conjured up for the question: “Technological innovation has thoroughly permeated countless facet of our existence, with the domain of education being no exception. In the midst of this exponentially evolving modernity of technological advancements, the dawn of generative artificial intelligence systems, have inaugurated a global debate regarding their integration and accessibility within education. Despite these avant-garde programmes, furnished with their prodigious yet arguably latent capacity to assimilate, generate, and customise content, bestowing upon students unparalleled opportunities for knowledge attainment and intellectual expansion; a cavalcade of potential pitfalls, ethical quandaries and pedagogical challenges that necessitate exhaustive academic scrutiny emerge. As we stand on the precipice of a new educational epoch, the widespread question emerges: Should students be granted boundless access to these systems? I contend that allowing students unfettered access to advanced AI tools could, contrary to expectations, impede educational progress and yield detrimental effects due to underlying ethical, scholastic, and developmental concerns. The quintessential contention in opposition to bestowing upon students unfettered access is firmly rooted in the principles aligned with academic integrity and the threat artificial intelligence constitutes to corroding any sense of it. Artificial intelligence systems, given their capabilities for content generation (contextually assignments/ essays etc.), could potentially facilitate an environment where original thought is negated yet supplanted by artificial intelligence generated responses, thereby calling into question the authenticity of ‘student- composed’ workings. (McCabe, et al., 2012) expound on the value of academic honesty as a cornerstone of educational institutions and learning processes whilst emphasising the principle that one’s work should be the product of one’s own understanding- an assertation of which I am wholly in accord with. Permitting students to the inexhaustible access of artificial intelligence programmes could undermine this tenet, as students may fabricate a grave dependence on generated material, thus impeding the cultivation of critical thinking and analytical abilities concurrently with invalidating any form of assessment process, which in theory is conceived to evaluate individual student learning and achievement (Newton, 2016). Such a dependency may involuntarily encourage a culture of lethargy and academic dishonesty (a culture of which I have personally bear witnessed where students would doubt and voluntarily omit their own academic facilities for insubstantial recapitulated artificially generated work), where plagiarism, not of texts, but ideas is conventional- subconsciously shifting the role of a student as an active learner to that of a passive regurgitator of generative artificial intelligence generated output; contributing to the devaluation of the educational process (Hughs & McCabe, 2006). Cognitive atrophy is a dormant threat in the scenario when enabling students to unlimited access to artificial intelligence generative programmes. Mechanisms of which may jeopardize and stifle the development of critical thinking and deep learning in students- two cornerstone objectives of education. Should students become overly dependent on artificial intelligence- this disproportionate dependence is also inversely proportional to compromising one’s prowess of maintaining prolonged concentration and introspective thought; there also lies a danger of fostering an ‘automation complacency’, a phenomenon whereby they (the students in question) subconsciously begin placing excessive trust in automated support, thereby attenuating their analytical rigor (Carr, 2011; Carr, 2014). To further accentuate this point, a study by (Sparrow, et al., 2011) found that people are less likely to retain information that is uncomplicatedly procurable online, suggesting that the ubiquitous nature of artificial intelligence could similarly affect memory and learning. Whilst being a computer science undergraduate at Cardiff Metropolitan University, we were tasked with devising and coding an optimised time complexity sorting algorithm. Delving into the intricacies of various sorting techniques, from bubble sort to selection sort to quicksort, this required substantial mental exertion and iteration. Though had we been given unrestricted access to the readily accessible assortment of modes of generative artificial intelligence, the looming temptation to simply generate the code would certainly have circumvented the valuable intellectual process of comparing efficiencies and leveraging algorithmic thinking. In accordance with (Bower & Sturman, 2015), educational technologies should be tools for the enhancement of learning, not substitutions for cognitive processes which in this example easily could have been the case. Data privacy/ security is another compelling argument against unbridled access to artificial intelligence systems. All platforms, whilst ostensibly altruistic in provisioning ‘free services’, operate within the data economy where user interactions are a commodity and gathered on an incomprehensible scale to tailor their outputs (Zuboff, 2019). Artificial intelligence platforms, necessitating an extensive trove of data in order to function optimally, not only raise concerns over data ownership and vulnerability but also emphasise that, as primary users, the student demographic inadvertently generates a considerable amount of ‘lucrative’ and sensitive personal data susceptible to commercial exploitation, security infringements, and identity theft (Solove, 2013; Zuboff, 2019). Rebuttals such as the following aforementioned render the notion of unconstrained access fundamentally at odds with, whilst simultaneously juxtaposing the ‘Privacy by Design’ (≅ data protection through technology design) principle (Cavoukian, 2009). This issue is further entangled by the nuances of informed consent; the more youthful student base may not possess the requisite depth of comprehending to providing informed consent pertaining to the use of their data whether it be for machine learning processes or not, in theory allowing artificial intelligence systems to capitalise on their naivety and erode personal autonomy in a realm where the sanctity of consent ought to be paramount (Roseenblat, et al., 2014). On the subject of data privacy/ security, I myself as someone who personally is averse to equipping students with unimpeded artificial intelligence access, reminisces on the reprehensible case of Facebook and the Cambridge Analytica scandals which servers as a stark reminder of the perils associated with vast data assemblages being mismanaged (Chadwalladr & Graham-Harrison, 2018).”