In questo elaborato ci siamo occupati del nudge, uno strumento di policy che può sostituire, o completare, i tradizionali tipi di intervento, quali tassazione e proibizione, con i vantaggi del minor costo e del mantenimento della libertà di scelta.
Abbiamo enunciato il concetto del nudge, i suoi principali ambiti di applicazione e descritto quali bias cognitivi sfrutta per essere efficace.
Inoltre, in risposta alle critiche etiche di manipolazione, abbiamo dimostrato che esso può essere efficace e trasparente al tempo stesso, in quanto la trasparenza non causa reattanza.
La ricerca futura sul nudge deve, quindi, più che concentrarsi su aspetti etici e di trasparenza, a mio parere, focalizzarsi su un altro problema che può minarne l’efficacia, ovvero l’eterogeneità. Come mostrato da vari studi sull’accettabilità, infatti, il nudge può dare risultati molto diversi in base a :
• L’ambito di applicazione (Jung e Mellers, 2016; Reynolds et al., 2019)
• Le caratteristiche delle persone, come l’età (Borghans e Golsteyn, 2015) o l’esperienza in materia (Löfgren et al., 2012) e le loro preferenze (Sunstein, 2015)
• Le caratteristiche dell’architetto della scelta, ad esempio se è il governo o un esperto in materia (Arad e Rubinstein, 2018)
• La nazione (Reisch e Sunstein, 2016; Sunstein, Reisch e Rauber, 2018; Sunstein, Reisch e Kaiser, 2019)
• Il partito politico sostenuto dalla persona (Tannenbaum, Fox e Rogers, 2017) • La tipologia di nudge, ad esempio se pro-self o pro-social (Hagman et al., 2015) • Se il nudge sfrutta processi cognitivi più o meno consci (Felsen, Castelo e Reiner, 2013;
Jung e Mellers, 2016; Sunstein, 2016a, 2016b) ed intrusivi (Diepeveen et al., 2013) Quindi, come sostenuto da Sunstein (2012) e Hagman et al. (2015), non vale il concetto di “one-nudge-fits-all” e la ricerca futura dovrebbe concentrarsi sul creare nudge sempre più personalizzati (vedi gli smart default di Smith et al., 2013), anche attraverso le nuove tecnologie e i Big Data (Yeung, 2017), in modo da massimizzare l’efficacia del nudge su ogni singolo individuo.
48
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