Visual attention can be considered as a selective filter that allows us to identify which stimuli to perceive, process and integrate in an environmental context to then be integrated into higher cognitive processes (1). Some authors have hypothesized the existence of an innate “social mind” since in typical developmental paths emerge attentional preferences and a spontaneous propensity towards salient social stimuli such as human faces (2). This early orientation towards the social is considered a crucial basis for language acquisition, emotional regulation and interpersonal understanding. For many years, atypical development has been attributed to a deviation from these early social attention patterns. In autistic people, a large body of studies has documented the emergence of attentional preferences often oriented towards non-social elements, peripheral details or specific perceptual aspects, rather than towards complex social scenes (3–6). These differences have been framed within models that attribute a reduced social motivation typical of people with autism (7) or to the inability to attribute mental states to others (8). New lines of research instead suggest that these attentional preferences may represent functional and adaptive strategies, shaped by peculiar neurological and perceptual configurations (9, 10). In this perspective, reduced attention to the face does not necessarily imply social disinterest, but may reflect a different way of processing information, based on criteria of predictability, structure and optimal sensory load (11). This perspective invites us to move beyond the idea of ​​a “normative” development as a univocal reference, promoting a more nuanced understanding of attentional differences as valid expressions of alternative cognitive architectures. In this context, digital technologies take on a central role as tools for ecological observation and personalized support. Technologies such as mobile eye-trackers, adaptive interfaces and immersive sensory environments allow not only to detect attention patterns in natural situations, but also to build tailor-made experiences that enhance individual resources and interests, promoting authentic involvement without imposing normative objectives (12–14). Introducing these tools right from the evaluation phase means not only improving the accuracy of clinical observation, but also redefining the intervention criteria, placing the emphasis not on correcting behavior, but on building paths that respect neurodivergent functioning, promoting well-being, autonomy and meaningful participation.

Longitudinal studies conducted with eye-tracking on infants later diagnosed with autistic neurodivergence detect a gradual decline in eye fixation times as early as 2 to 6 months of age (15), so divergent patterns of visual attention may be detectable even before formal diagnosis. Moreover, such atypical patterns have been mainly attributed to social stimuli such as faces and gestures as opposed to high-contrast geometric patterns and visually predictable stimuli (16, 17). Studies on neurodevelopmental condition, particularly autism spectrum disorder (ASD), confirm the precociousness of attentional deficits (18), which explains the impaired interaction with social stimuli and consequently the development of social cognition and corresponding networks. Difficulties are found in processing social cues such as emotional expression (19–21) and gaze (22–24), as well as in abstracting invariant features necessary for facial recognition (25–27), in fact, in experimental settings, children and adults with ASD often pay attention to faces while not extracting the same crucial information from faces as individuals with typical development (18). For many autistic people divergence, social stimuli represent unpredictable or overstimulating stimuli therefore they are inclined to develop a natural tendency to favor more stable and structured visual elements in their surroundings. Can this tendency of theirs affect their development, are people with autistic divergence less socially engaged because they pay attention differently or do they pay attention differently because stimuli, especially social stimuli, are less rewarding or more cognitively challenging?

The dominant view of atypical visual attention in autistic people is based on the concept of deficit because it is believed that decreased attention to social stimuli reflects a lack of interest, impaired social cognition, or a delay in the development of shared intentionality. Therefore, joint attention or gaze training has been developed, although this could risk simplifying a complex phenomenon or ignoring the inner logic of autistic cognition. A more nuanced interpretation, however, recognizes that attentional differences may reflect a valid rather than pathological perceptual style. For example, increased attention to more static objects or patterns could be a compensatory strategy that facilitates predictability and reduces cognitive load in sensorially overloaded or socially ambiguous environments (28). Reframing the concept could therefore have different implications for both research and clinical practice, as if interventions that aim to “normalize” visual behavior might not consider the underlying sensory and emotional costs. A strengths-based approach, on the other hand, should understand the individual attentional profile and build intervention strategies based on it. Reframing visual attention in autism as divergent rather than deficit opens new avenues for both scientific inquiry and clinical innovation. This approach involves an appreciation of neurodiversity and an understanding of attentional differences as such, not just as precursors to pathology, but as alternative, coherent, and meaningful ways of interacting with the environment (29, 30), although specific enhancement should not be lacking. This involves shifting attention toward a neurodiversity-centered rather than pathologizing view, so that perceptual atypicality is studied for what it is, and not just for what it lacks relative to an assumed norm (31). Interventions that aim only at correcting rather than capturing the strengths of people with autism are shown, based on what has been analyzed, to be less effective than those that make use of visual and/or textual supports and personal interests (32). Thus, it is important to recognize and understand attention differences so that they are not perceived as obstacles, but specific aspects on which to set intervention. To do this, clinical practice and research are today called upon to equip themselves with tools capable of detecting and enhancing these perceptive modalities in their real context: digital technologies offer, in this sense, new opportunities.

Within a clinical perspective oriented towards neurodiversity, digital technologies represent promising tools not to normalize, but to understand and support the spontaneous attentional modalities of autistic people. In particular, the use of technologies such as portable eye-trackers, immersive sensory environments, adaptive interfaces and interactive applications allows us to observe and support attention in an ecological, respectful and personalized way. For example, the use of mobile eye-tracking in natural contexts (such as home or school) allows to detect spontaneous attentional patterns in a non-invasive way, offering valuable data on where and how attention is distributed without forcing the person to rigid or potentially stressful tasks. This information can be used to build individual attentional profiles, useful for designing targeted interventions that integrate visual interests, preferred sensory channels and the need for predictability of stimuli. In parallel, the use of adaptive educational apps or digital interfaces capable of modulating content based on detected attention patterns can enhance learning and communication starting from the specific perceptive functioning of the user. In this way, attention is not forced towards normative objectives (e.g. eye contact), but accompanied in the direction of individual interests and resources. Studies such as that of Powell et al. (33) have shown that training with gaze-contingent eye-tracking improves sustained attention without forcing the gaze towards the face, but adapting to the cognitive functioning mode of each child. Even in the therapeutic field, controlled multisensory environments – such as Snoezelen rooms or immersive platforms – allow for the safe testing of different stimulus-response configurations, observing how attention varies in relation to light intensity, auditory stimuli, movement or the presence of simulated social elements. This dynamic evaluation supported by technology allows for the identification of optimal activation and regulation conditions, paving the way for truly personalized interventions. The integration of digital technologies into clinical practice can profoundly transform the way in which we observe and work with autistic attention: from an element to be corrected to a resource to be understood, supported and valorized. This change of perspective also implies a review of clinical objectives, efficacy criteria and the role of technology itself. The following table synthetically compares the traditional approach, centered on normalization, with the one informed by neurodiversity, which aims to valorize individual profiles (See Table 1):

The characteristics of visual attention in autism must be read as an adaptive and consistent expression of divergent perceptual modalities to be in line with an innovative perspective of research and clinical intervention. The attentional differences observed in the early stages of development are not necessarily indicative of social disinterest or impairment, but may reflect spontaneous strategies to manage sensory complexity, cognitive load and the unpredictability of social stimuli (28, 31). In the digital era, new technologies can play an important role in favoring the transition towards a new understanding in supporting and enhancing attentional skills in autism by moving from being tools aimed at normalizing behavior (e.g., increasing eye contact) to means to observe, understand and improve individual attentional trajectories (34). This allows for the construction of personalized interventions that do not impose a normative model, but that adapt to the sensory and motivational profile of the person (32, 35). From a clinical point of view, it means moving from interventions focused on the “correction” of attention (such as gaze training) to practices that enhance its communicative and regulatory functionality. Using visual supports, predictable environments, stimuli related to interests and an experiential design sensitive to sensory load not only increases effectiveness, but reduces the risk of stress, masking and failure to recognize individual identity (10). The conscious integration of technology paves the way for dynamic assessment and therapy models, which are not limited to measuring static behaviors, but follow the evolution of attention over time and contexts, offering tools to build authentic and sustainable therapeutic and educational relationships. Adopting a perspective centered on neurodiversity, supported by technologies that respect individual functioning, therefore means redefining the criteria of clinical efficacy, placing at the center not forced adaptation, but autonomy, well-being and the valorization of the perceptive and cognitive resources of each person.