Emerging technologies are unlocking new possibilities for gathering and leveraging data from personal devices to provide highly customized and contextualized user experiences. As Dr. Poppy Crum, CTO, and neuroscientist, highlighted in her Technology and Human Evolution presentation at TIBCO Next, this shift towards data-driven personalization presents exciting opportunities to enhance quality of life across domains.
The same input can result in vastly different perceptions and responses among people based on physiological differences, experiences, and situational context. As Dr. Crum illustrated, two people can look at an identical image yet have completely distinct interpretations. Accessing more channels of personal data can help close this perceptual gap.
With the ubiquity of sensors and the rise of AI, companies now have unprecedented means to gather and analyze information from individuals’ behaviors, bodies, and environments. This digital exhaust or “situational intelligence” enables much richer customization.
Quality and value depend on the frequency and resolution of input data. Ask, what’s the added value? We have learned that if 17 minutes of a long-haul driver’s time with driven assistance monitoring, we will not have a driver shortage. In construction, 40% of what happens is rework — fixing mistakes. Effective digital twins with daily or more frequent scanning enables intelligence access to reduce rework by more than 90%. Digital twins in hospitals have led to 25-minute treatment savings per patient, improving the patient’s quality of care and revenue for the hospital. Digital twin models have enabled a 65% improvement in aerosol delivery efficiency, making highly personalized drug delivery more efficacious.
The health of the ecosystem depends on the data intelligence we have about the system and our ability to go from insight to action. Here are several opportunities.
Next-Generation Digital Twins
Detailed real-time representation of physical environments informed by diverse data streams can optimize performance. For instance, data-rich digital twins of reef ecosystems enabled far healthier reefs by informing and facilitating preventive care.
By understanding users’ cognitive states, stressors, and goals, technology can better align with human needs instead of optimizing for the wrong metrics. For example, smart home devices can track mood to adjust lighting and music for comfort rather than pure energy efficiency.
Truly Personalized Experiences
With sufficient personal data signals, experiences can be tailored to match individual users’ changing contexts, abilities, and preferences at a moment in time. One-size-fits-all technology will become obsolete.
Continuous biometrics from consumer wearables may identify medical conditions like Parkinson’s, dementia, and Multiple Sclerosis years earlier than before based on digital biomarkers in speech and motion. Voice analysis can even detect COVID-19 infections.
Cognitive Load Tracking
Pupil dilation, micro-expressions, and tone of voice can reveal cognitive effort and emotional state. This enables optimization of information delivery for easier comprehension and task focus.
Subconscious Response Monitoring
Sensors capturing galvanic skin response, breathing rate, and brain waves uncover reactions below conscious awareness. These insights enable the design of technology and experiences that better resonate at a neurological level.
Challenges and Considerations
While personalized data holds huge potential to enhance our technology experiences and quality of life, it also raises serious privacy concerns. Gathering extensive data on individuals’ behaviors, bodies, and emotions necessitates clear consent, transparency, and stringent data privacy safeguards. Users must retain agency over if and how their personal data is collected and applied.
There are also risks if organizations use personalization irresponsibly or if algorithmic biases taint insights. Flawed implementations can feel invasive rather than empowering. Technologists must carefully assess and address potential harms. Extensive testing with diverse users in real environments is essential to avoid pitfalls.
A Balance of Art and Science
At its best, highly customized technology experiences rooted in users’ unique data signatures will feel magical — responsive to needs we didn’t even know we had. But poor executions devoid of humanity in pursuit of total personalization could damage trust and adoption.
Navigating this balance requires care, ethics, and close partnership between technologists, users, and domain experts. If done thoughtfully, Dr. Crum believes emerging sensing capabilities and AI advances can usher in “a bespoke revolution” elevating personalized human experiences in all parts of life and business. But the details matter immensely, and the stakes could not be higher. We must get the balance right.
A Roadmap Forward
So, how can technologists adopt personalized data responsibly? Several best practices can help guide development:
- Prioritize transparency: Clearly communicate what data is gathered and how it is applied. Provide users with control options.
- Validate with research: Rigorously test new sensing capabilities and personalization algorithms before deployment to ensure they work equitably for diverse populations.
- Champion privacy: Engineer privacy protections and consent into the core experience, not as an afterthought. Enable anonymity where possible.
- Curb overreach: Collect the minimum data needed. Avoid surveillance-capitalism business models dependent on excessive user data gathering.
- Spotlight ethics: Convene internal and external ethics advisory boards to construct guardrails for data usage. Conduct impact assessments.
- Cultivate trust: Personalization should feel assistive rather than creepy. Set under promising goals focused on delighting users rather than pursuing total predictive accuracy.
- Empower agency: Provide transparent controls allowing user data restrictions and opt-outs. Make personalization adjustable and optional.
- Enlist domain experts: Work closely with researchers in relevant fields (e.g., neuroscience, psychology, medicine) to validate data application.
- Learn continuously: Monitor for unintended consequences and feedback. Be ready to adjust course. Depersonalization or misuse of sensitive inference techniques may require stepping back.
Personal data can undoubtedly enable more helpful, responsive, and delightful technology experiences. But thoughtfully balancing innovation and ethics will be critical as these capabilities evolve. If we embrace lessons from early efforts, develop open, collaborative frameworks, and keep users’ real needs and consent in the driver’s seat, the future looks bright.
Dr. Crum ended with this quote:
When a flower doesn’t bloom, you fix the environment in which it grows, not the flower — or maybe we do both.
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