AI, autonomous machines and human awareness: Towards shared machine-human contexts in medicine

The AAAI 2019 Spring Series was held Monday through Wednesday, March 25–27, 2019 on the campus of Stanford University, adjacent to Palo Alto, California. The titles of the nine symposia were Artificial Intelligence, Autonomous Machines, and Human Awareness: User Interventions, Intuition and Mutually Constructed Context; Beyond Curve Fitting — Causation, Counterfactuals and Imagination-Based AI; Combining Machine Learning with Knowledge Engineering; Interpretable AI for Well-Being: Understanding Cognitive Bias and Social Embeddedness; Privacy- Enhancing Artificial Intelligence and Language Technologies; Story-Enabled Intelligence; Towards Artificial Intelligence for Collaborative Open Science; Towards Conscious AI Systems; and Verification of Neural Networks.

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The Dark Side of Artificial Intelligence: Challenges for the Legal System

Southern African Public Law ◽

10.25159/2522-6800/6979 ◽

2020 ◽

Vol 35 (1) ◽

Author(s):

Willem Gravett

Keyword(s):

Artificial Intelligence ◽

Legal System ◽

Indirect Effects ◽

Current Trend ◽

Dark Side ◽

Work Practices ◽

Direct And Indirect Effects ◽

Autonomous Machines ◽

State Surveillance

The development of artificial intelligence has the potential to transform lives and work practices, raise efficiency, savings and safety levels, and provide enhanced levels of services. However, the current trend towards developing smart and autonomous machines with the capacity to be trained and make decisions independently holds not only economic advantages, but also a variety of concerns regarding their direct and indirect effects on society as a whole. This article examines some of these concerns, specifically in the areas of privacy and autonomy, state surveillance, and bias and algorithmic transparency. It concludes with an analysis of the challenges that the legal system faces in regulating the burgeoning field of artificial intelligence.

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Ritual Impurity in Tannaitic Literature: Two Opposing Perspectives

Journal of Ancient Judaism ◽

10.30965/21967954-00101005 ◽

2010 ◽

Vol 1 (1) ◽

pp. 65-103

Author(s):

Vered Noam

Keyword(s):

Entire System ◽

Natural Laws ◽

Natural Substance ◽

Actual Existence ◽

Human Awareness

This paper examines the rabbinic concept of impurity in terms of the essence of the reality that this term implies. Did the Rabbis consider impurity to be a force of nature, or rather an abstract formalistic structure devoid of any actual existence? A review of rabbinic sources regarding corpse impurity reveals that the essential structures of tannaitic halakhah are grounded in a natural, immanent perception of impurity, which gave rise to an entire system, intricate and coherent, of “natural laws of impurity.” Layered onto this system, as a secondary stratum of sorts comprising exceptions and “addenda,” is a more subtle halakhic tapestry woven from a diametrically opposed perception. This view subjects the concept of impurity to human awareness and intention, severing it from reality and, in so doing, also stripping it of its “natural” substance.

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A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station

Sensors ◽

10.3390/s21041178 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1178

Author(s):

Bo Sun ◽

Bo Tan ◽

Wenbo Wang ◽

Elena Simona Lohan

Keyword(s):

Mean Squared Error ◽

Signal To Noise Ratio ◽

Time Estimation ◽

Satellite System ◽

Base Station ◽

Rectangular Array ◽

Single Station ◽

5G Network ◽

Autonomous Machines ◽

3D Positioning

The 5G network is considered as the essential underpinning infrastructure of manned and unmanned autonomous machines, such as drones and vehicles. Besides aiming to achieve reliable and low-latency wireless connectivity, positioning is another function provided by the 5G network to support the autonomous machines as the coexistence with the Global Navigation Satellite System (GNSS) is typically supported on smart 5G devices. This paper is a pilot study of using 5G uplink physical layer channel sounding reference signals (SRSs) for 3D user equipment (UE) positioning. The 3D positioning capability is backed by the uniform rectangular array (URA) on the base station and by the multiple subcarrier nature of the SRS. In this work, the subspace-based joint angle-time estimation and statistics-based expectation-maximization (EM) algorithms are investigated with the 3D signal manifold to prove the feasibility of using SRSs for 3D positioning. The positioning performance of both algorithms is evaluated by estimation of the root mean squared error (RMSE) versus the varying signal-to-noise-ratio (SNR), the bandwidth, the antenna array configuration, and multipath scenarios. The simulation results show that the uplink SRS works well for 3D UE positioning with a single base station, by providing a flexible resolution and accuracy for diverse application scenarios with the support of the phased array and signal estimation algorithms at the base station.

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