Mind-reading devices are revealing the brain’s secrets

Naddaf, Miryam

doi:10.1038/d41586-024-00481-2

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…As the terminology varies in different communities, there is no consensus on how to label sets two and three; the first set is named "training" set in the machine learning community, and "calibration" set within chemometrics. And even if a complex model performs well on a test set, there is no guarantee that the model is robust toward prediction of unseen data Ball (2023), Naddaf (2024).…”

Section: Model Validationmentioning

confidence: 99%

A retrospective view on non-linear methods in chemometrics, and future directions

Westad,

Flåten

2024

Front. Anal. Sci.

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This perspective article reviews how the chemometrics community approached non-linear methods in the early years. In addition to the basic chemometric methods, some methods that fall under the term “machine learning” are also mentioned. Thereafter, types of non-linearity are briefly presented, followed by discussions on important aspects of modeling related to non-linear data. Lastly, a simulated data set with non-linear properties is analyzed for quantitative prediction and batch monitoring. The conclusion is that the latent variable methods to a large extent handle non-linearities by adding more linear combinations of the original variables. Nevertheless, with strong non-linearities between the X and Y space, non-linear methods such as Support Vector Machines might improve prediction performance at the cost of interpretability into both the sample and variable space. Applying multiple local models can improve performance compared to a single global model, of both linear and non-linear nature. When non-linear methods are applied, the need for conservative model validation is even more important. Another approach is pre-processing of the data which can make the data more linear before the actual modeling and prediction phase.

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Section: Model Validationmentioning

confidence: 99%

A retrospective view on non-linear methods in chemometrics, and future directions

Westad,

Flåten

2024

Front. Anal. Sci.

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Mind-reading in AI and neurotechnology: evaluating claims, hype, and ethical implications for neurorights

Gilbert,

Russo

2024

AI Ethics

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This paper examines claims that the convergence of AI and neurotechnology applications, known as brain-reading, enables the reading of human minds. The purpose of this examination is to investigate whether the use of the terms “brain-reading” and “mind-reading” to convey current neurotechnological findings carries evidence of hype. We conducted an interpretive content analysis of 1017 academic articles to gain insights into the current state of the art and examine assertions made by academics. Our analysis revealed that up to 91% of the examined articles suggest the possibility of mind-reading through brain-reading. Ethical issues discussed frequently include mental privacy, mental freedom, and personhood. Our study highlights the imprecise and inconsistent usage of the term mind-reading in scientific discourse, which leads to exaggerated claims about AI and BCIs having already achieved capacities beyond their current capabilities—or even reaching capacities that may never be feasible. While our study provides evidence of AI and BCI hype concerning alleged mind-reading capabilities, it also uncovers a hype in AI ethics, specifically pertaining to neurorights. This involves hypothetical scenarios where the fictional prospect of AI-enabled mind-reading calls for the establishment of new protective human rights.

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Beyond the extended and distributed ‘self’: from subliminal extended selves to nonlocality and neurocapitalism

Tadajewski

2024

Journal of Marketing Management

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Mind-reading devices are revealing the brain’s secrets

Cited by 3 publications

References 13 publications

A retrospective view on non-linear methods in chemometrics, and future directions

A retrospective view on non-linear methods in chemometrics, and future directions

Mind-reading in AI and neurotechnology: evaluating claims, hype, and ethical implications for neurorights

Beyond the extended and distributed ‘self’: from subliminal extended selves to nonlocality and neurocapitalism

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