AI lit­er­acy, which refers to "a set of skills that enable a sol­id under­stand­ing" (Cas­al-Otero et al. 2023) of the tech­no­logy, is deemed a cru­cial com­pet­ence for both cur­rent and future learners (e.g. Long & Magerko 2020). Espe­cially in the realm of know­ledge work, prac­tic­al know­ledge about and the influ­ence of gen­er­at­ive AI appear par­tic­u­larly per­tin­ent (Chui et al. 2023). How­ever, the rela­tion­ship between gen­er­at­ive AI and know­ledge is com­plic­ated due to the con­ten­tious semant­ic status of AI-gen­er­ated texts (Bend­er et al. 2021). Apart from copy­right issues and biases in train­ing data, texts and images pro­duced by gen­er­at­ive AI lack con­cern for accur­acy and can thus be char­ac­ter­ized as “bull­shit" (Frank­furt 2005). Con­sequently, attain­ing AI lit­er­acy should involve com­pre­hend­ing the implic­a­tions that gen­er­at­ive AI func­tions as an almost inex­haust­ible mech­an­ism for pro­du­cing text and images, pos­sibly without inten­tion­al­ity, mor­al, eth­ic­al, or fac­tu­al con­trol.

Rhet­or­ic presents a prom­ising strategy to address these chal­lenges. The rhet­or­ic­al pro­duc­tion of texts, argu­ments, and topoi inher­ently pos­sesses a machine-like qual­ity (Brown Jr. 2014), bear­ing sub­stan­tial sim­il­ar­ity to the mode of pro­duc­tion of gen­er­at­ive AI. At the same time, as a con­sequence of his­tor­ic­al cri­ti­cism dat­ing back to Pla­to, rhet­or­ic as an edu­ca­tion­al dis­cip­line has fostered strin­gent guidelines to counter alleg­a­tions of arbit­rar­i­ness in its meth­od­o­lo­gies. Util­iz­ing rhet­or­ic as ped­agogy can enrich under­stand­ing of gen­er­at­ive AI, facil­it­at­ing more effect­ive integ­ra­tion into edu­ca­tion­al con­texts. This neces­sit­ates edu­ca­tion­al restruc­tur­ing, entail­ing redefined teach­er roles, spe­cified and refined stu­dent skills, and poten­tially the incor­por­a­tion of AI tutors as assist­ants.

The pan­el, there­fore, aims to explore why know­ledge about AI should encom­pass not only tech­nic­al aspects but also how rhet­or­ic­al lit­er­acy can con­trib­ute to and enhance the concept of AI lit­er­acy in learn­ing envir­on­ments. Speak­er one's con­tri­bu­tion estab­lishes a con­nec­tion between AI lit­er­acy and rhet­or­ic­al lit­er­acy, and by employ­ing rhet­or­ic­al con­cepts such as imit­a­tio auctor­um and doxa, illus­trates why per­ceiv­ing gen­er­at­ive AI as a rhet­or­ic­al sys­tem can be bene­fi­cial from a learn­ing stand­point. With this rhet­or­ic­al frame­work in mind, we will delve into the instruc­tion­al implic­a­tions of gen­er­at­ive AI con­cern­ing the acquis­i­tion of present­a­tion com­pet­ence. Speak­ers 2 and 3 both exam­ine the rela­tion­ship between gen­er­at­ive AI and the rhet­or­ic­al format of present­a­tions by sec­ond­ary school stu­dents in STEM sub­jects. Speak­er 2's focus will be on the role of the teach­er as a rhet­or­ic­ally trained guide, while speak­er 3 will dis­cuss the mean­ing of rhet­or­ic­al con­trol over gen­er­at­ive AI tools from a student's per­spect­ive, emphas­iz­ing rhet­or­ic­al prompt­ing and reflect­ive ana­lys­is. To con­clude the pan­el, speak­er 4 offers reflec­tions on AI func­tion­ing as an inde­pend­ent rhet­or­ic­al tutor and its implic­a­tions for eth­os con­struc­tion in sim­u­lated com­mu­nic­a­tion scen­ari­os, using Chat­G­PT as an illus­tra­tion.


Dr. Markus Gott­schling: “Trans­former Rhet­or­ic: Using rhet­or­ic­al prin­ciples to under­stand gen­er­at­ive AI”
Cen­ter for Rhet­or­ic­al Sci­ence Com­mu­nic­a­tion Research on Arti­fi­cial Intel­li­gence (Uni­ver­sity of Tübin­gen, Ger­many)
markus.gottschling@uni-tuebingen.de

Maria Föt­tinger: “Cyber­net­ic Instruc­tion, Con­struct­iv­ism and Gen­er­at­ive AI in Con­cert — The Teach­er as Rhet­or­ic­al Helms­man for Devel­op­ing Present­a­tion Com­pet­ence in Sec­ond­ary School Stu­dents with Gen­er­at­ive AI Tools”
maria.foettinger@uni-tuebingen.de
Present­a­tion Research Unit at the Research Cen­ter for Sci­ence Com­mu­nic­a­tion (Uni­ver­sity of Tuebin­gen, Ger­many)

Dr. Fabi­an Ruth: “Do gen­er­at­ive AI tools change the present­a­tion pre­par­a­tion of sec­ond­ary school stu­dents? Instruc­tion­al implic­a­tions for the com­pet­ent use of gen­er­at­ive AI for suc­cess­ful present­a­tions.“
fabian.ruth@uni-tuebingen.de
Present­a­tion Research Unit at the Research Cen­ter for Sci­ence Com­mu­nic­a­tion (Uni­ver­sity of Tuebin­gen, Ger­many)

Anna-Mar­ie Köhler & Salina Weber: “Chat­G­PT as an ideal tutor? A ques­tion of eth­os”. 
anna-marie.koehler@uni-tuebingen.de, salina.weber@uni-tuebingen.de
Cen­ter for Rhet­or­ic­al Sci­ence Com­mu­nic­a­tion Research on Arti­fi­cial Intel­li­gence (Uni­ver­sity of Tübin­gen, Germany)