In September 2024, California quietly set a precedent. Lawmakers passed SB 1223, an amendment to the California Consumer Privacy Act (CCPA) that classifies neural data as “sensitive personal information.” For the first time in U.S. law, brain-derived signals such as electroencephalography (EEG) traces, functional MRI (fMRI) scans (a type of MRI imaging that measures and maps brain activity) or brain-computer interface (BCI) activity are treated as a category apart from other forms of biodata. The move may seem technical, but it signals a new public expectation: if companies intend to touch the brain, they will be held to stricter standards of stewardship, purpose limitation, and user control.
This is a threshold moment for neuroethics. It invites us to move beyond dystopian speculation about mind-reading machines and focus instead on what neurotechnology can actually do today, how it already intersects with a broader data economy, and what values should shape its future. The challenge is not just to minimize harm, but to make choices that expand human flourishing rather than reduce us to more efficient workers or more predictable consumers.
As we advance toward developing a new generation of BCIs, it is essential that we do so with the highest ethical standards. There are three key ethical dilemmas associated with the deployment of new generations of BCIs: the risks of “neuroexceptionalism”, making closed loops contestable, and balancing productivity with human flourishing.
The risks of neuroexceptionalism
Cochlear implants, deep brain stimulation, and other BCIs have been part of medicine since the 1980s. Fueled by those early wins, a constant stream of fMRI studies and an active portrayal in the arts, neurotechnology has done an amazing job at marketing itself. The field has sold us on the vision that BCI could read our inner thoughts and control our brains, causing significant concern for many. This has led to the concept of “neuroexceptionalism”, the notion that brain data is uniquely threatening, unlike any other kind of personal information.
The truth is more sobering. Progress in BCI research is incremental, constrained by biology, engineering, and clinical validation. By contrast, the real threats to autonomy are already embedded in mature digital ecosystems. Heart-rate monitors, location histories, click trails, and engagement metrics can expose and shape behavior with remarkable accuracy, at global scale, right now. This was evident in Google’s acquisition of Fitbit. In 2020, the European Commission approved the deal only on the condition that Google would silo Fitbit health data and not use it for targeted advertising. What restrained Google was not ethics but antitrust law. The implication is alarming: if we fear biometric manipulation, heart-rate variability may be a more practical vector today than speculative EEG-based mind-reading.
None of this means neural data requires less protection. Quite the opposite: it means we must integrate what we’ve learned from the tech age into digital oversight. Neurotech deserves rigorous governance, but it cannot be regulated in a vacuum. We should not over-index on speculative future risks while ignoring the proven influence mechanisms already operating across the digital stack.
The recent announcement of Sam Altman’s investment in Merge Labs illustrates the tension. In response to this, experts and online pundits are now warning us against tech giants using gene therapy to come after our brains. However, the real asymmetry of power lies in how they can already monetize the mundane signals of daily life. Does some of the information that users are voluntarily donating to OpenAI in using ChatGPT as their assistant/therapist/consultant qualify as brain data?
Making closed loops contestable
Closed-loop BCIs are systems that read neural activity, process it, and deliver targeted stimulation, leading to more effective control. An example of this are neuroprosthetics designed to treat epilepsy by predicting seizures and delivering electrical stimulation that prevent their propagation. They also raise worries: could such loops covertly shape behavior?
Social media platforms monitor clicks, algorithmically tailor what comes next, and optimize endlessly for engagement. Cambridge Analytica’s role in elections was not a theoretical risk, it was proof that closed behavioral feedback loops already exist, powered not by electrodes but by content feeds.
Propaganda and manipulation are nothing new. The printing press triggered an explosion of information and disinformation centuries ago. Ever since, the responsibility has fallen to media and civic leaders to ensure populations were educated enough to resist manipulation. Social media has shown, over the last decade, just how effective targeted influence can be on a mass scale. Unlike web-based feedback loops, neurotech might bypass the user’s conscious filters. There’s not self-imposed protection, you’re going straight to the source. It’s the difference between propaganda and pointing a gun at someone’s thoughts.
The question, then, is not whether closed loops exist in the cortex or on a smartphone screen, but whether those loops are transparent, auditable, and contestable. Neurotechnology should not repeat the mistakes of social media. It must be designed from the outset with audit trails, clear safety limits, and accountability. Stimulation policies should be treated as safety-critical, subject to the same kinds of testing and logs that govern aviation or pharmaceuticals.
Balancing productivity with human flourishing
BCIs could, in theory, make people type faster, learn quicker, or work longer. However, this would only extend the treadmill of today’s consumer technologies, which push us to produce harder and then collapse into distraction.
A richer horizon is to expand access to what philosophers once called “the good life”: creativity, play, aesthetic depth, social connection, and awe. Imagine BCIs that heighten music’s emotional resonance, make collaborative art more immersive, or make rehabilitation more motivating, not as byproducts but as central design goals.
Newcastle University’s Neudio project points in this direction. By syncing music to neural activity, the aim is not curing depression or boosting productivity, but simply amplifying the emotional punch of a song. BCI enhancement may be better measured in goosebumps per second, not words per minute.
What next? Choosing what to value
If we get ethics right at this slow stage, before adoption outruns reflection, then California’s SB 1223 amendment to the Consumer Privacy Act will be remembered not as the end of a debate, but as the start of a more imaginative one.
The central question is not just how to minimize risks. It is what to value. Do we want technologies that treat our brains like mines to be extracted, or like gardens to be cultivated? Do we want conformity and control, or flourishing and difference? Human creativity has always driven technology toward diversity, subculture, and play. Even with something as powerful as BCIs, there is reason to believe that variety over uniformity will prevail.
As we move forward in the field, I invite key opinion leaders to reach out so we can discuss the future of ethics in BCI.
Picture: Getty Images, wigglestick
Cyril Eleftheriou is the neurotech lead at Subsense, leading R&D in visual neuroscience, interface biology, and precision imaging for the company’s non-surgical, nanoparticle-based brain-computer interface. Formerly a Principal Scientist at Novartis, he brings over 15 years of experience spanning the U.K., Italy, and the U.S. in neuro-electronic interfacing, advanced imaging, and retinal regeneration. His research has ranged from gene therapy and nanoparticle biologics to multiphoton microscopy and neural circuit mapping. At Subsense, Cyril applies his multidisciplinary expertise to advance seamless mind-machine communication and redefine how humans interact with technology through safe, scalable, non-invasive neural interfaces.
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