If you’re happy an AI won’t know it

Nelson Mail - - COMMENT&OPINION - OLIVER MOODY The Times

When Siri, the au­to­mated iPhone as­sis­tant, is ques­tioned about the mean­ing of hap­pi­ness, it says: ‘‘Hap­pi­ness: men­tal or emo­tional state of well-be­ing char­ac­terised by pleas­ant emo­tions.’’

‘‘Siri,’’ The Times asked, ‘‘am I happy?’’ ‘‘No com­ment,’’ it replied.

Re­search sug­gests that Siri is not the only in­tel­li­gent as­sis­tant that strug­gles with the mys­ter­ies of hu­man joie de vivre. Rus­sian com­puter sci­en­tists have de­vel­oped an al­go­rithm that is able to pick up hints of calm and anger from peo­ple’s voices, but is largely flum­moxed by the sound of a good mood.

The study has echoes of Marvin, the su­per-in­tel­li­gent but pro­foundly depressed ro­bot from the Hitch­hiker’s Guide to the Gal­axy books, who once said that his ca­pac­ity for hap­pi­ness could be fit­ted in­side a match­box ‘‘with­out tak­ing out the matches first’’.

Re­searchers are try­ing to give com­put­ers the abil­ity to de­tect peo­ple’s emo­tions from the sound of their speech, the words they choose or their fa­cial ex­pres­sions. These skills will be im­por­tant if ro­bots and ar­ti­fi­cial in­tel­li­gence (AI) pro­grams are to be­gin rou­tinely in­ter­act­ing with hu­mans in sen­si­tive set­tings such as the han­dling of cus­tomer com­plaints.

Sci­en­tists in Ger­many have de­signed an an­i­mated 3D avatar called Greta that can recog­nise the traces of some emo­tions in the hu­man voice and re­flect them on her face. At Stanford Univer­sity, Cal­i­for­nia, re­searchers have built soft­ware that can de­tect 14 feel­ings in­clud­ing pride, bore­dom and con­tempt, although it is cor­rect only about half the time.

Sci­en­tists at Rus­sia’s Na­tional Re­search Univer­sity’s Higher School of Eco­nomics cam­pus in Nizhny Nov­gorod have achieved an over­all ac­cu­racy of 71 per cent for eight emo­tions, rang­ing from dis­gust to sur­prise.

Most re­search has pre­vi­ously used an ap­proach known as fea­ture se­lec­tion, in which com­put­ers look for par­tic­u­lar pat­terns of sound linked to emo­tions. Alexan­der Pono­marenko and his col­leagues took a dif­fer­ent tack, turn­ing voices into a vis­ual for­mat called a spec­tro­gram. ‘‘It can be ap­plied in some sys­tems like Siri and Alexa,’’ Dr Pono­marenko said.

The sys­tem in­ter­preted record­ings of 24 ac­tors read­ing phrases in dif­fer­ent emo­tions. It was good at de­tect­ing calm, dis­gust and neu­tral speech, but could spot hap­pi­ness only 45 per cent of the time. The emo­tion was of­ten con­fused with fear and anger.

‘‘Un­for­tu­nately the model has some dif­fi­cul­ties sep­a­rat­ing happy and an­gry emo­tions,’’ the sci­en­tists wrote. ‘‘Most likely the rea­son for this is that they are the strong­est emo­tions, and as a re­sult their spec­tro­grams are slightly sim­i­lar.’’

The re­search is pub­lished in a book is­sued by the In­ter­na­tional Con­fer­ence for Neu­roin­for­mat­ics.

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