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Large generative AI models (GMs) like GPT and DALL-E are trained to generate content for general, wide-ranging purposes. GM content filters are generalized to filter out content which has a risk of harm in many cases, e.g., hate speech. However, prohibited content is not always harmful -- there are instances where generating prohibited content can be beneficial. So, when GMs filter out content, they preclude beneficial use cases along with harmful ones. Which use cases are precluded reflects the values embedded in GM content filtering. Recent work on red teaming proposes methods to bypass GM content filters to generate harmful content. We coin the term green teaming to describe methods of bypassing GM content filters to design for beneficial use cases. We showcase green teaming by: 1) Using ChatGPT as a virtual patient to simulate a person experiencing suicidal ideation, for suicide support training; 2) Using Codex to intentionally generate buggy solutions to train students on debugging; and 3) Examining an Instagram page using Midjourney to generate images of anti-LGBTQ+ politicians in drag. Finally, we discuss how our use cases demonstrate green teaming as both a practical design method and a mode of critique, which problematizes and subverts current understandings of harms and values in generative AI. 

Motor learning in visuomotor adaptation tasks results from both explicit and implicit processes, each responding differently to an error signal. Although the motor output side of these processes has been extensively studied, the visual input side is relatively unknown. We investigated if and how depth perception affects the computation of error information by explicit and implicit motor learning. Two groups of participants made reaching movements to bring a virtual cursor to a target in the frontoparallel plane. The Delayed group was allowed to reaim and their feedback was delayed to emphasize explicit learning, whereas the camped group received task-irrelevant clamped cursor feedback and continued to aim straight at the target to emphasize implicit adaptation. Both groups played this game in a highly detailed virtual environment (depth condition), leveraging a cover task of playing darts in a virtual tavern, and in an empty environment (no-depth condition). The delayed group showed an increase in error sensitivity under depth relative to no-depth. In contrast, the clamped group adapted to the same degree under both conditions. The movement kinematics of the delayed participants also changed under the depth condition, consistent with the target appearing more distant, unlike the Clamped group. A comparison of the delayed behavioral data with a perceptual task from the same individuals showed that the greater reaiming in the depth condition was consistent with an increase in the scaling of the error distance and size. These findings suggest that explicit and implicit learning processes may rely on different sources of perceptual information. NEW & NOTEWORTHY We leveraged a classic sensorimotor adaptation task to perform a first systematic assessment of the role of perceptual cues in the estimation of an error signal in the 3-D space during motor learning. We crossed two conditions presenting different amounts of depth information, with two manipulations emphasizing explicit and implicit learning processes. Explicit learning responded to the visual conditions, consistent with perceptual reports, whereas implicit learning appeared to be independent of them. 

Transition metal interactions with Lewis acids (M → Z linkages) are fundamentally interesting and practically important. The most common Z-type ligands contain boron, which contains an NMR active 11 B nucleus. We measured solid-state 11 B{ 1 H} NMR spectra of copper, silver, and gold complexes containing a phosphine substituted 9,10-diboraanthracene ligand (B 2 P 2 ) that contain planar boron centers and weak M → BR 3 linkages ([(B 2 P 2 )M][BAr F 4 ] (M = Cu (1), Ag (2), Au (3)) characterized by large quadrupolar coupling ( C Q ) values (4.4–4.7 MHz) and large span ( Ω ) values (93–139 ppm). However, the solid-state 11 B{ 1 H} NMR spectrum of K[Au(B 2 P 2 )] − (4), which contains tetrahedral borons, is narrow and characterized by small C Q and Ω values. DFT analysis of 1–4 shows that C Q and Ω are expected to be large for planar boron environments and small for tetrahedral boron, and that the presence of a M → BR 3 linkage relates to the reduction in C Q and 11 B NMR shielding properties. Thus solid-state 11 B NMR spectroscopy contains valuable information about M → BR 3 linkages in complexes containing the B 2 P 2 ligand. 

The water reactivity of the boroauride complex ([Au(B 2 P 2 )][K(18-c-6)]; (B 2 P 2 , 9,10-bis(2-(diisopropylphosphino)-phenyl)-9,10-dihydroboranthrene) and its corresponding two-electron oxidized complex, Au(B 2 P 2 )Cl, are presented. Au(B 2 P 2 )Cl is tolerant to H 2 O and forms the hydroxide complex Au(B 2 P 2 )OH in the presence of H 2 O and triethylamine. [Au(B 2 P 2 )]Cl and [Au(B 2 P 2 )]OH are poor Lewis acids as judged by the Gutmann–Becket method, with [Au(B 2 P 2 )]OH displaying facile hydroxide exchange between B atoms of the DBA ring as evidenced by variable temperature NMR spectroscopy. The reduced boroauride complex [Au(B 2 P 2 )] − reacts with 1 equivalent of H 2 O to produce a hydride/hydroxide product, [Au(B 2 P 2 )(H)(OH)] − , that rapidly evolves H 2 upon further H 2 O reaction to yield the dihydroxide compound, [Au(B 2 P 2 )(OH) 2 ] − . [Au(B 2 P 2 )]Cl can be regenerated from [Au(B 2 P 2 )(OH) 2 ] − via HCl·Et 2 O, providing a synthetic cycle for H 2 evolution from H 2 O enabled by O–H oxidative addition at a diboraanthracene unit. 

The boron-centered reactivity of the diboraanthracene-auride complex ([Au(B2P2)][K(18-c-6)]; (B2P2, 9,10-bis(2-(diisopropylphosphino)- phenyl)-9,10-dihydroboranthrene) with a series of organic carbonyls is reported. The reaction of [(B2P2)Au]– with formaldehyde or paraformaldehyde results in a head-to-tail dimerization of two formaldehyde units across the boron centers. In contrast, the reaction of [(B2P2)Au]– with two equivalents of benzaldehyde yields the pinacol coupling product via C–C bond formation. Careful stoichiometric addition of one equivalent of benzaldehyde to [Au(B2P2)]– enabled the isolation of an adduct corresponding to the formal [4+2] cycloaddition of the C=O bond of benzaldehyde across the boron centers. This adduct reacts with a second equivalent of benzaldehyde to produce the pinacol coupling product. Finally, the reaction of [Au(B2P2)]– with acetone results in a formal reductive deoxygenation with discrete hydroxo and 2-propenyl units bound to the boron centers. This reaction is proposed to proceed via an analogous [4+2] cycloadduct, highlighting the unique small molecule activation chemistry available to this platform. 

Visually guided movements can show surprising accuracy even when the perceived three-dimensional (3D) shape of the target is distorted. One explanation of this paradox is that an evolutionarily specialized “vision-for-action” system provides accurate shape estimates by relying selectively on stereo information and ignoring less reliable sources of shape information like texture and shading. However, the key support for this hypothesis has come from studies that analyze average behavior across many visuomotor interactions where available sensory feedback reinforces stereo information. The present study, which carefully accounts for the effects of feedback, shows that visuomotor interactions with slanted surfaces are actually planned using the same cue-combination function as slant perception and that apparent dissociations can arise due to two distinct supervised learning processes: sensorimotor adaptation and cue reweighting. In two experiments, we show that when a distorted slant cue biases perception (e.g., surfaces appear flattened by a fixed amount), sensorimotor adaptation rapidly adjusts the planned grip orientation to compensate for this constant error. However, when the distorted slant cue is unreliable, leading to variable errors across a set of objects (i.e., some slants are overestimated, others underestimated), then relative cue weights are gradually adjusted to reduce the misleading effect of the unreliable cue, consistent with previous perceptual studies of cue reweighting. The speed and flexibility of these two forms of learning provide an alternative explanation of why perception and action are sometimes found to be dissociated in experiments where some 3D shape cues are consistent with sensory feedback while others are faulty. NEW & NOTEWORTHY When interacting with three-dimensional (3D) objects, sensory feedback is available that could improve future performance via supervised learning. Here we confirm that natural visuomotor interactions lead to sensorimotor adaptation and cue reweighting, two distinct learning processes uniquely suited to resolve errors caused by biased and noisy 3D shape cues. These findings explain why perception and action are often found to be dissociated in experiments where some cues are consistent with sensory feedback while others are faulty. 

Abstract Humans can operate a variety of modern tools, which are often associated with different visuomotor transformations. Studies investigating this ability have shown that separate motor memories can be acquired implicitly when different sensorimotor transformations are associated with distinct (intended) postures or explicitly when abstract contextual cues are leveraged by aiming strategies. It still remains unclear how different transformations are remembered implicitly when postures are similar. We investigated whether features of planning to manipulate a visual tool, such as its visual identity or the environmental effect intended by its use (i.e. action effect) would enable implicit learning of opposing visuomotor rotations. Results show that neither contextual cue led to distinct implicit motor memories, but that cues only affected implicit adaptation indirectly through generalization around explicit strategies. In contrast, a control experiment where participants practiced opposing transformations with different hands did result in contextualized aftereffects differing between hands across generalization targets. It appears that different (intended) body states are necessary for separate aftereffects to emerge, suggesting that the role of sensory prediction error-based adaptation may be limited to the recalibration of a body model, whereas establishing separate tool models may proceed along a different route.