The Ethics of Life as It Could Be: Do We Have Moral Obligations to Artificial Life?

The field of Artificial Life studies the nature of the living state by modeling and synthesizing living systems. Such systems, under certain conditions, may come to deserve moral consideration similar to that given to nonhuman vertebrates or even human beings. The fact that these systems are nonhuman and evolve in a potentially radically different substrate should not be seen as an insurmountable obstacle to their potentially having rights, if they are sufficiently sophisticated in other respects. Nor should the fact that they owe their existence to us be seen as reducing their status as targets of moral concern. On the contrary, creators of Artificial Life may have special obligations to their creations, resembling those of an owner to their pet or a parent to their child. For a field that aims to create artificial life-forms with increasing levels of sophistication, it is crucial to consider the possible ethical implications of our activities, with an eye toward assessing potential moral obligations for which we should be prepared. If Artificial Life is larger than life, then the ethics of artificial beings should be larger than human ethics.

A Survey of Recent Practice of Artificial Life in Visual Art.

Nowadays, interdisciplinary fields between Artificial Life, artificial intelligence, computational biology, and synthetic biology are increasingly emerging into public view. It is necessary to reconsider the relations between the material body, identity, the natural world, and the concept of life. Art is known to pave the way to exploring and conveying new possibilities. This survey provides a literature review on recent works of Artificial Life in visual art during the past 40 years, specifically in the computational and software domain. Having proposed a set of criteria and a taxonomy, we briefly analyze representative artworks of different categories. We aim to provide a systematic overview of how artists are understanding nature and creating new life with modern technology.

Chemical Systems for Wetware Artificial Life: Selected Perspectives in Synthetic Cell Research.

The recent and important advances in bottom-up synthetic biology (SB), in particular in the field of the so-called "synthetic cells" (SCs) (or "artificial cells", or "protocells"), lead us to consider the role of wetware technologies in the "Sciences of Artificial", where they constitute the third pillar, alongside the more well-known pillars hardware (robotics) and software (Artificial Intelligence, AI). In this article, it will be highlighted how wetware approaches can help to model life and cognition from a unique perspective, complementary to robotics and AI. It is suggested that, through SB, it is possible to explore novel forms of bio-inspired technologies and systems, in particular chemical AI. Furthermore, attention is paid to the concept of semantic information and its quantification, following the strategy recently introduced by Kolchinsky and Wolpert. Semantic information, in turn, is linked to the processes of generation of "meaning", interpreted here through the lens of autonomy and cognition in artificial systems, emphasizing its role in chemical ones.

The emergence of dynamic networks from many coupled polar oscillators: a paradigm for artificial life.

This work concerns a many-body deterministic model that displays life-like properties such as emergence, complexity, self-organization, self-regulation, excitability and spontaneous compartmentalization. The model portraits the dynamics of an ensemble of locally coupled polar phase oscillators, moving in a two-dimensional space, that under certain conditions exhibit emergent superstructures. Those superstructures are self-organized dynamic networks, resulting from a synchronization process of many units, over length scales much greater than the interaction range. Such networks compartmentalize the two-dimensional space with no a priori constraints, due to the formation of porous transport walls, and represent a highly complex and novel non-linear behavior. The analysis is numerically carried out as a function of a control parameter showing distinct regimes: static pattern formation, dynamic excitable networks formation, intermittency and chaos. A statistical analysis is drawn to determine the control parameter ranges for the various behaviors to appear. The model and the results shown in this work are expected to contribute to the field of artificial life.

Regulative development as a model for origin of life and artificial life studies.

Using the formal framework of the Free Energy Principle, we show how generic thermodynamic requirements on bidirectional information exchange between a system and its environment can generate complexity. This leads to the emergence of hierarchical computational architectures in systems that operate sufficiently far from thermal equilibrium. In this setting, the environment of any system increases its ability to predict system behavior by "engineering" the system towards increased morphological complexity and hence larger-scale, more macroscopic behaviors. When seen in this light, regulative development becomes an environmentally-driven process in which "parts" are assembled to produce a system with predictable behavior. We suggest on this basis that life is thermodynamically favorable and that, when designing artificial living systems, human engineers are acting like a generic "environment".

Emergence in Artificial Life.

Even when concepts similar to emergence have been used since antiquity, we lack an agreed definition. However, emergence has been identified as one of the main features of complex systems. Most would agree on the statement "life is complex." Thus understanding emergence and complexity should benefit the study of living systems. It can be said that life emerges from the interactions of complex molecules. But how useful is this to understanding living systems? Artificial Life (ALife) has been developed in recent decades to study life using a synthetic approach: Build it to understand it. ALife systems are not so complex, be they soft (simulations), hard (robots), or wet(protocells). Thus, we can aim at first understanding emergence in ALife, to then use this knowledge in biology. I argue that to understand emergence and life, it becomes useful to use information as a framework. In a general sense, I define emergence as information that is not present at one scale but present at another. This perspective avoids problems of studying emergence from a materialist framework and can also be useful in the study of self-organization and complexity.

[Synthetic biology: from "build-for-use" to commercialization].

The convergence of advances in chemistry, physics, mathematics, computer science, and engineering into life science research gives rise to synthetic biology. Synthetic biology adopts the concept and strategy of engineering science research, aiming at redesigning and reprogramming the existing biological systems, designing and constructing new bio-bricks such as enzymatic parts, genetic circuits, and chassis cells, or even creating non-natural functions of "artificial life". Synthetic biology promotes the leap from understanding of life to design of life, and is revolutionizing biotechnology and sustainable development of bioeconomy. Via this retrospective review of Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, the most representative research entity focusing on "build-for-use" of synthetic biology in China, this article summarizes the important scientific and technological breakthroughs and industry impacts in the past decade, and prospects future development of synthetic biology in China.

[Digital cell models and their applications: a review].

Various omics technologies are changing Biology into a data-driven science subject. Development of data-driven digital cell models is key for understanding system level organization and evolution principles of life, as well as for predicting cellular function under various environmental/genetic perturbations and subsequently for the design of artificial life. Consequently, the construction, analysis and design of digital cell models have become one of the core supporting technologies in synthetic biology. This paper summarized the research progress on digital cell models in the last ten years after the foundation of Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, with a focus on the development and quality control of genome-scale metabolic network for reliable metabolic pathway design and their application in guiding strain metabolic engineering. We also introduced the latest progress on developing cellular models with multiple constraints to improve prediction accuracy. At last, we briefly discussed the current challenges and future directions in digital cell model development. We believe that digital cell technology, along with genome sequencing, genome synthesis and genome editing, will greatly improve our ability in reading, writing, modifying and creating life.

Knowledge, attitudes, and practices towards drug-food interactions among patients at public hospitals in eThekwini, KwaZulu-Natal, South Africa

Background: Drug-food interactions can lead to adverse drug reactions and therapy failure which can potentially impact patient safety and therapy outcome. Objectives: This study assessed patients' knowledge, attitudes and practices regarding drug-food interactions. Methods: A cross-sectional study was conducted among patients at three public hospitals in eThekwini, KwaZulu-Natal. Statistical analysis was performed using SPSS® version 25. The association between demographic variables and patients' knowledge, attitudes and practices were assessed. Results: Of the 342 patients, 70.5% were female, and the mean age was 42.87±0.89 years. Almost 50% of patients had secondary level education, and 64% were unemployed. About 52% of patients had high knowledge of drug-food interactions; however, only 30-50% of the patients could identify potential drug-food interactions of their drugs. More than half of the patients (51.5%) answered that they took multivitamin pills with medications and 61.7% responded they consulted healthcare professionals for drug-food interactions' information before taking new medications. Few patients (15.2%) had experienced drug-food interactions. Conclusions: Overall, patients had gaps in their knowledge and practices, and positive attitudes towards drug-food interactions. Many patients could not identify food items that can potentially interact with their drugs. It is important that education and medication counselling are provided to patients to prevent drug-food interactions, ensure optimal drug therapy and patient safety