A Is For Another: A Dictionary Of AI

Origi­nal website here

A Is For Anot­her answers the ques­tion: what is AI? Or, how do we unders­tand what it means to be human and non-human through arti­fi­cial inte­lli­gence? This dicti­o­nary presents how inte­lli­gence, humans, machi­nes, data and mind exist across a vari­ety of cosmo­lo­gies, scien­ces and art prac­ti­ces as percep­ti­ons change over time.

This project 

This project focu­ses on a parti­cu­lar aspect of AI: that it is shaped in terms of the human. So while AI is about machine lear­ning, cogni­tion and robots, it is also about how we unders­tand what it means to be human, how our noti­ons of the human, and of the non-human, are chan­ging over time, as are our inter-rela­ti­ons­hips. We want to show that ‘inte­lli­gen­ce’, ‘humans’, ‘machi­nes’, ‘data’ and ‘mind’ exist diffe­rently across a vari­ety of cosmo­lo­gies, scien­ces, and prac­ti­ces. A Is For Anot­herputs diverse scho­lars­hip, art and cultu­ral work in conver­sa­tion with each other to further this thin­king.

Arti­fi­cial Inte­lli­gence, ‘AI’,  is a suite of tech­no­lo­gies that inclu­des machine lear­ning, compu­ter vision, reaso­ning, and natu­ral language proces­sing, among others. It exists in an awkward and unique space as tech­no­logy, metap­hor and socio-tech­ni­cal imagi­nary

In 1987, a compu­ter was consi­de­red ‘inte­lli­gent’ because it beat the world’s highest ranked chess player. Now, a compu­ter will be consi­de­red inte­lli­gent if it can drive a car; or because it gene­ra­tes a response based on your facial expres­sion. Inte­lli­gence beco­mes a moving target defi­ned by tasks like percep­tion, pattern recog­ni­tion, language proces­sing or predic­tion. What is served by this idea?

Now, AI’s compo­nent tech­no­lo­gies are employed in object recog­ni­tion, language trans­la­tion and recom­men­der systems, among others, crea­ting novel mani­fes­ta­ti­ons of exis­ting perso­nal, social and poli­ti­cal rela­ti­ons.

Metap­hors and narra­ti­ves serve as shor­thand for navi­ga­ting new situ­a­ti­ons and tech­no­lo­gies. The history of science shows us that we use metap­hors to describe somet­hing unfa­mi­liar and new, and this beco­mes entan­gled in how we study it, thus shaping the arte­fact in terms of its metap­hor. Phra­ses like ‘infor­ma­tion just wants to be free’ or ‘data is the new oil’ have shaped what we think digi­tal tech­no­lo­gies are. Such metap­hors deter­mine how a tech­no­logy is deve­lo­ped, built, and will be regu­la­ted (or not regu­la­ted). For exam­ple, if you imagine arti­fi­cial inte­lli­gence tech­no­lo­gies as a child, a non-human species like an octo­pus or a mythi­cal crea­ture like a Centaur, then how will you regu­late it?

A Is For Anot­her is a response to the world-making and cultu­rally homo­ge­nous appro­a­ches to AI emer­ging from places like Sili­con Valley and Holly­wood. For exam­ple, in the Euro­pean/US/UK Science Fiction genre, robots gene­rally convey an anxi­ety about the displa­ce­ment or erasure of human beings. The beau­ti­ful, calcu­la­ting fembot Eva in Ex Machina or the thre­a­te­ning synt­he­tic inte­lli­gence Skynet in Termi­na­tor are such compe­lling fanta­sies.

The inter­ac­tion between pop culture, cosmo­lo­gies and the robo­tics industry in Japan presents a diffe­rent kind of ‘robo­tic imagi­nary’ (Rhee). And ‘robot’ is only one word for this fasci­na­ting and drama­tic non-human/human being. Tokyo Cyber­punk presents a panoply of vivid post­hu­man pop-cultu­ral figu­res nego­ti­a­ting specu­la­tive socio-poli­ti­cal scena­rios, “explor[ing] new possi­bi­li­ties of beco­ming at the rhizo­ma­tic inter­sec­tion of diffe­rent forms of inte­lli­gence, corpo­re­a­lity, and data proces­sing.”

Also, with Jenni­fer Rhee we ask of robots and all things AI: “How does this figure engage the histo­ries of under- valued, deva­lued, and exploi­ted labor, parti­cu­larly as they inter­sect with race, gender, and class? Who is being dehu­ma­ni­zed in this robot figure? Whose human­ness is cons­truc­ted as fami­liar and sacro­sanct?” So what happens when we read a history of inte­lli­gence from the pers­pec­tive of Cogni­tive Psycho­logy along­side a social-mate­ri­a­list inquiry into the women who were known as compu­ters?

Or consi­der that mush­ro­oms and robots, both non-human enti­ties, are equally subjects of the Post­hu­ma­ni­ties; Anna Tsing’s ethno­graphy of Matsu­take culti­va­tion has been an inspi­ra­ti­o­nal text for many entries here. Howe­ver, Alexan­der Wehe­liye and Sylvia Wynter have writ­ten very diffe­rent histo­ries of ‘non-humans’, and the cate­gory of ‘man’, through the lens of Trans­at­lan­tic slavery, colo­ni­a­lism and colo­nial plan­ta­ti­ons. Simi­larly, futu­risms- Afro-futu­rismGulf-futu­rism– are synt­he­ses of geopo­li­tics with pop-culture, and psycho­ge­o­grap­hies of bodies moving forwards and back in time and space, both online and off. What imagi­na­ries of auto­ma­tion, bodies, data and inte­lli­gence exist here? 

The purpose of this project is not to advance a new theo­re­ti­cal rati­o­nale for how AI could or should be desig­ned. Nor does it describe how tech­no­lo­gies like machine lear­ning or compu­ter vision work in the world, how they demons­trate bias, if they have ethics or not, or might be used to address the climate catas­trophe. There are many resour­ces about AI on these topics online. 

Instead, we want to create forks and distrac­ti­ons in how ‘AI’ is being imagi­ned and produ­ced in the world.

This Website

A tradi­ti­o­nal online search assu­mes that a seeker alre­ady knows what they are looking for and can type it into a box. But as Mitchell White­law tells us: "Search is unge­ne­rous: it with­holds infor­ma­tion, and demands a query…” His gene­rous inter­fa­ces appro­ach suggests an alter­na­tive: “rich, brow­sa­ble inter­fa­ces that reveal scale and comple­xity.”

Padmini and Pratyush — the desig­ners of this website — applied White­law’s appro­ach to reflect my own jour­ney of lear­ning about AI’s [other] dimen­si­ons and futu­res: mean­de­ring, seren­di­pi­tous, non-linear. This process has invol­ved reading about the history of AI as docu­men­ted in offi­cial archi­ves; visi­ting art exhi­bi­ti­ons and cultu­ral events and atten­ding lectu­res; inter­ac­ting with futu­ro­lo­gists imagi­ning auto­no­mous cars through animal inte­lli­gence, and so on. It has been both bewil­de­ring and illu­mi­na­ting — and not all connec­ti­ons are strong; some­ti­mes the path is more inter­es­ting than where you end up. 

This process has prima­rily invol­ved sear­ching online; but using the inter­net for rese­arch is a tricky exer­cise. There are paywalls (and ways to get around them, some­ti­mes), a struc­tu­ral poli­tics to who crea­tes know­ledge online, and closely-guar­ded, propri­e­tary algo­rithms cura­ting what will appear higher up in your search results. Human cura­tors and guides have been essen­tial to my wayfin­ding by making mate­rial avai­la­ble, and sugges­ting connec­ti­ons to domains of know­ledge not all of which appear rela­ted to each other at first glance. 

What do these jour­neys look like when trans­po­sed onto a digi­tal expe­ri­ence? 

The grid view is like the fami­liar expe­ri­ence of consul­ting a dicti­o­nary: soli­tary, speci­fic and top-down. It compri­ses cura­ted, unique and whim­si­cal entries offe­ring diffe­rent pers­pec­ti­ves on huma­nity and AI. Each entry is a body of text with hyper­links to refe­ren­ces outside this website. 

The rela­ti­o­nal view is a visu­a­li­sa­tion of all these refe­ren­ces toget­her. Every refe­ren­ce’s hyper­link is assig­ned a hand­ful of tags; for exam­ple: ‘non-human’, 'ecology’, ‘post­hu­ma­nism’, or ‘robots’. These tags are visu­a­li­sed as yellow bubbles; the larger the bubble, the more refe­ren­ces asso­ci­a­ted with that tag. Clic­king on a tag bubble reve­als smaller white bubbles that link out to that refe­rence. The tag bubbles them­sel­ves are not clic­ka­ble. Pratyush has program­med vari­ous cues into the visu­a­li­sa­tion to orient you to your jour­ney through the mate­rial. The visu­a­li­sa­tion works best when viewed on a desk­top screen.

Compa­ring the grid and rela­ti­o­nal views, we might say that the grid view is like swim­ming in a pool, and the rela­ti­o­nal view is like swim­ming out into the ocean. In the words of Anna Tsing, this is not a “logi­cal machine” but an “open-ended assem­blage”; it “gesture[s] to the so-much-more-out-there.”

This dicti­o­nary is neit­her exhaus­tive nor compre­hen­sive. It is a snaps­hot of small and situ­a­ted data aggre­ga­ted over years of summer scho­ols, works­hops and semi­nars. This dicti­o­nary is not closed either; it is open to mate­rial that takes this thin­king to new places. There is space for new entries, colla­bo­ra­tion and further rese­arch and peda­gogy, so please get in touch: hello at aisfo­ra­not­her dot net

Maya Indira Ganesh. Berlin, April 2020

This Project

This Website

Grid View

Rela­ti­o­nal View

Credits

Maya Indira Ganesh. Berlin, April 2020