Accountability for ML failures

, 59–60

navigating complexity of accountability

, 59–60

Actuarial inference

, 30

Advanced encryption techniques

, 63

Advanced ML algorithms

, 56

Adversarial debiasing

, 28–29, 41, 43

Algae biofuels

, 125

Algorithmic biases

, 40–41

in education

, 31

Algorithmic decision systems (ADS)

, 29

domains of

, 29–35

Algorithmic systems

, 29

Algorithmic transparency and bias

, 54

Aliens

, 178–181

life

, 178–180

moral transition into world with

, 185–194

Antarctic programs

, 216

Anthropocene, targeting of technologies of

, 162–166

Anticipation

, 178–181

Artificial General Intelligence (AGI)

, 18, 85

Artificial intelligence (AI)

, 3, 9–10, 28, 43–44, 52, 105–106, 113–114

AI-based algorithms

, 33

AI-enabled robots

, 72–74

AI-powered systems

, 114

AI-powered technologies

, 52

consciousness and

, 140–141

empathy and

, 141–152

ethics

, 100, 102, 149, 151

higher education and

, 144–146

history of

, 137–140

industry

, 55

navigating coexistence of AI-enabled coworkers

, 72–73

open questions

, 151–152

rise of AI-enabled coworkers in manufacturing

, 72

systems

, 57

Artificial intelligence Fairness 360 (AIF360)

, 28–29, 42–43

Artificial neural networks

, 52

Artificial womb

, 222–223, 225

Asimov’s laws of robotics

, 11, 18, 21

application on hypothesised real-case contemporary situation

, 14–18

application on imagined future scenarios

, 18–21

directed at humans

, 13–14

responsibility

, 12–13

Asteroid capture tech

, 164

Augmented and virtual reality (AR/VR)

, 52

challenge of privacy in

, 60–62

data privacy and security in AR/VR Systems

, 62–64

ethical framework for AR/VR technologies in industry

, 65–66

ethical implications of AR/VR in industrial production

, 60–66

examples

, 60–62

psychological effects

, 64–65

psychological impacts and gamification in AR/VR

, 64–65

Autonomy

, 65

Baseline Random Forest model

, 44

Benign failure modes

, 86

Biases

, 28, 31–32, 40–42

Bioastronautics

, 4

Bioethics

, 139–140, 151–152, 224

AI open questions

, 151–152

epharmology

, 146–148

ethics of using AI

, 149–151

first problematic intermezzo

, 140–141

higher education and AI

, 144–146

history of AI

, 137–140

problematic intermezzo

, 141–152

Biofuels

, 124–127

Biomedical human enhancement

, 202, 209

Biosafety, issue of

, 127–128

Biosecurity, issue of

, 128–129

Biotechnology

, 3–4, 173–174

“Bottom-up” approach

, 98–100

Capitalism

, 208–210

Case Management Inventory (CMI)

, 36

Chat Generative Pre-Trained Transformer (ChatGPT)

, 139–140, 145, 151

Civil Rights movement

, 160

Classical approach

, 205

Cognitive biases

, 33–34

Cohen’s approach

, 181–182

Coherent Extrapolated Volition (CEV)

, 89

Collaborative manufacturing tasks

, 71–72

Collaborative robots (cobots)

, 71

Collaborative work environments, transition to

, 72–73

Colonization

, 107–108, 115

of lifeworld

, 105–106

Communicative action

, 108–110

Computational framework

, 28–29

Computational intelligence

, 112–113

Conference of the Parties (COP)

, 120–121

Confidence

, 15

Consciousness and AI

, 140–141

Control

, 13

Cooperative interpretation process

, 109

Correctional Offender Management Profiling for Alternative Sanctions (COMPAS)

, 35–36, 39

algorithm

, 28, 43–44

model

, 40

problems with

, 42–43

tool

, 35–36

Cosmic radiation

, 218

COVID-19 pandemic

, 219

Criminal justice in age of AI

algorithmic biases and debiasing

, 40–41

domains of algorithmic decision systems

, 29–35

problems with COMPAS algorithm

, 42–43

ProPublica’s Study COMPAS

, 39–40

recidivism risk assessment instruments

, 35–39

Criticality of reliable ML

, 57

Cyberphysical integration, ethical challenges in

, 68

Cyberphysical systems, ethical landscape of digital twins as

, 66–68

Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI)

, 52

Data anonymization

, 64

Data gathering processes

, 53

Data privacy and security in AR/VR systems

, 62–64

challenge of privacy in AR/VR landscape

, 62–63

risks of personal data misuse

, 63

securing AR/VR data

, 63–64

Debiasing

, 40–41

Decision-making process

, 52

Deep learning models

, 56, 138–139

Dehumanization concerns in workplace

, 75

Democracy

, 14

Digital technology

, 105–106

Digital twins

, 52

ethical challenges in cyberphysical integration

, 68

ethical framework for digital twin technology

, 70

ethical implications of digital twins in manufacturing

, 66–70

ethical landscape of digital twins as cyberphysical systems

, 66–68

role of digital twins in manufacturing

, 67–68

Digitization

concept of digitizing human aspects

, 68–69

of human elements and implications

, 68–70

potential risks and ethical concerns

, 69–70

of social behaviour

, 110

Discrimination

, 32

Disparate Impact Remover

, 44–45

Double-edged sword

, 65

Dragon Systems from Massachusetts

, 138

Dual-process approaches

, 181–182

Earth, human enhancement and vulnerable people on

, 205–209

Ectogenesis

, 223

potential benefits of using ectogenesis for space settlements

, 222–223

Education

, 31

Empathy and AI

, 141–152

Energy production

, 124–127

Engineering

, 1

Epharmology

, 3–4, 146, 148

Ethical framework

for digital twin technology

, 70

for human–robot collaboration

, 75–76

Ethical Management of AI (EMMA)

, 55

Ethical reflection

, 2

Ethics (see also Bioethics)

, 114–115

of knowledge

, 129

of using AI

, 149–151

European Parliament

, 11

European Union (EU)

, 130–131

Ex-vivo Uterine Environment platform (EVE platform)

, 222–223

Exclusion

, 32

Explainable AI (XAI)

, 55–57

Exploitation

, 202–205

Extensions

, 90–93

of prophecy

, 90–91

Extraterrestrial life

monster

, 181, 185, 194–195

moral transition into world with aliens

, 185–194

outer space, monsters, aliens, anticipation and moral imagination

, 178–181

Extrauterine Environment for Neonatal Development (EXTEND)

, 222–223

Fairness

, 28

Feature selection methods

, 34

Federal Food, Drug, and Cosmetics Act (FDCA)

, 130–131

Federal Law on Insecticides, Fungicides, and Rodenticides (FIFRA)

, 130–131

Feminist bioethics

, 205–206, 211–212

Future

, 1

Futures Literacy Laboratory-Novelty (FLL-N)

, 186–187

Gamification in AR/VR

, 64–65

Gap

, 1–2

Gender exclusion

, 208–209

Gene editing

, 202–203, 211–212

Generative Adversarial Network (GAN)

, 41

Generative AI

, 112

Geoengineering

, 172

Geosynchronous orbit (GEO)

, 162–163

Global bioethics

, 205–206

Gradient Penalty

, 44

Gravity fields

, 220–221

Habermas

, 105–106

Health service

, 206

Higher education and AI

, 144–146

Historical Clinical Risk Management-20 (HCR-20)

, 36

Horizontal gene transfer (HGT)

, 124, 126, 128

Human enhancement

and type of space mission and rationale

, 203–205

and vulnerable people in space

, 209–211

and vulnerable people on Earth

, 205–209

Human nature

, 202–203, 205

Human Resource (HR)

, 33

Human-centric approach

, 65

Human–robot collaboration (HRC)

, 52

ethical framework for

, 75–76

safeguarding physical and psychological health in

, 73–74

socio-economic implications of

, 74–75

Humans, navigating coexistence of

, 72–73

Hypothesised real-case contemporary situation, application on

, 14–18

Immune function

, 221

In-process tweaks

, 34

Indiana Risk Assessment System (IRAS)

, 36

Industrial Revolution

, 112

Industry, ethical framework for AR/VR technologies in

, 65–66

Industry 4.0 technologies

, 52

Information systems

, 32

Information-based ‘mechanization’ process

, 114

Informed consent

, 224

Institutional sexism and positioning of women’s bodies as “problem”

, 216–217

Instrumental convergence thesis

, 88

Intelligent machines

, 112–113

Intelligent manufacturing systems

, 52, 55–56, 77

advent of AI and intelligent manufacturing

, 51–53

charting ethical course in intelligent manufacturing

, 76–77

dehumanization concerns in workplace

, 75

digitization of human elements and implications

, 68–70

ensuring personnel safety

, 73–74

ethical considerations in machine learning in manufacturing

, 53–60

ethical dimensions of human–robot collaboration in manufacturing

, 70–76

ethical framework for digital twin technology

, 70

ethical framework for human–robot collaboration

, 75–76

ethical implications of AR/VR in industrial production

, 60–66

ethical implications of digital twins in manufacturing

, 66–70

ethical landscape of digital twins as cyberphysical systems

, 66–68

examples

, 71–72

examples in manufacturing

, 66

navigating coexistence of humans and AI-enabled coworkers

, 72–73

potential job displacement and inequality

, 74–75

psychological impacts

, 74

rise of AI-enabled coworkers in manufacturing

, 72

safeguarding physical and psychological health in HRC

, 73–74

socio-economic implications of HRC

, 74–75

transition to collaborative work environments

, 72–73

Intensions

, 90–93

of prophecy

, 90–91

International Energy Agency (IEA)

, 125

International Genetically Engineered Machine (iGEM)

, 127–128

International organizations (UNESCO)

, 150

Interstellar craft

, 164

Justice concept

, 28

Justification

, 169–170

Kiesling’s process

, 123–124

Knowledge

, 108

Large language models (LLMs)

, 139–140

Laws of Robotics

, 9–10

Learning

, 148

Lebenswelt

, 106–110

future, AI and ethical factor

, 113–114

intelligent machines

, 112–113

and technology

, 110–114

unbearable complexity of

, 112–113

Legacy of Socrates

, 98–102

Level of Service Inventory-Revised (LSI-R)

, 36–37

Level of Service/Case Management Inventory (LS/CMI)

, 36

Liberal democracy

, 173

Life

, 122–123

Lifeworld

, 108–109

colonization

, 107–108

communicative action

, 108–110

Lebenswelt

, 106–110

Lebenswelt and technology

, 110–114

unbearable complexity of Lebenswelt

, 112–113

Liminality

, 185

Local Interpretable Model-agnostic Explanations (LIME)

, 42

Low Earth Orbit (LEO)

, 162–163, 215–216

Machine learning (ML)

, 28, 43–44, 52

accountability for ML failures

, 59–60

algorithms

, 16

ethical considerations in machine learning in manufacturing

, 53–60

examples

, 53–54

imperative of proactive ethical engagement

, 55

key ethical challenges in ML-integrated manufacturing

, 54–55

models

, 66, 112

reliability of ML systems

, 57–59

tools

, 33

transparency in ML systems

, 55–57

Malignant failure modes

, 86

Manufacturing

ethical implications of digital twins in

, 66–70

rise of AI-enabled coworkers in

, 72

role of digital twins in

, 67–68

Mechanization

, 112

Memex

, 138

Micro-gravity

, 218

Military tensions

, 172

Minimal genome project

, 122–123

Ministry’s Code of Ethics

, 10

Mission

, 204–205

Monster

, 178, 181, 185, 194–195

theory

, 178

Monsterization

, 178–180

Moral exceptionalism

, 203

Moral imagination

, 178–181

Moral sensitivity

, 180

Morality

, 114–115

Mycoplasma mycoides

, 122–123

National Aeronautics and Space Administration (NASA)

, 216–217

National Bioeconomy Blueprint 2012 report, The

, 120–121

National space agencies

, 216

Natural Language Processing (NLP)

, 33

New Space

, 203–204

Nonviolent Risk Assessment (NVRA)

, 37

Nuclear technology

, 173–174

Off-world human society

, 217

Off-world pregnancy risks

, 217–222

distance from Earth

, 219–220

gravity fields

, 220–221

hostile/closed environments

, 221–222

isolation and confinement

, 219

space radiation

, 218–219

Offender Assessment System (OASys)

, 37

Ohio Risk Assessment System (ORAS)

, 37

Open-source AI models

, 57

Outer space

, 178–181

Outer Space Treaty, The

, 163

Partial merger of space skepticism with political activism

, 168–171

Perils of synthetic biology

artificial life from scratch

, 122–123

efficient manufacturing of pharmaceuticals

, 123–124

energy production

, 124–127

ethical issues of

, 127–129

history of

, 121–123

issue of biosafety

, 127–128

issue of biosecurity

, 128–129

potential benefits and ethical issues of

, 123–129

synthetic biology

, 120–121

synthetic biology regulation

, 130–131

Personal data misuse, risks of

, 63

Personnel safety

, 73–74

Perverse instantiation

aligning intensions and extensions

, 90–93

genies once and genies in future

, 93–98

legacy of Socrates

, 98–102

twisting wishes and instantiating

, 86–90

Perverse instantiation

, 95–97

Pharmaceuticals, efficient manufacturing of

, 123–124

Philosophical method of Socrates

, 92

Physical health in HRC

, 73–74

Political activism, partial merger of space skepticism with

, 168–171

Populism

, 164

Post Conviction Risk Assessment tool (PCRA tool)

, 38

Post-processing approaches

, 34

Pre-processing

, 34

Pregnancy

, 221

Prejudice

, 32

Principles for Supervision of Synthetic Biology

, 130

Proactive ethical engagement, imperative of

, 55

Promises of synthetic biology

artificial life from scratch

, 122–123

efficient manufacturing of pharmaceuticals

, 123–124

energy production

, 124–127

ethical issues of

, 127–129

history of

, 121–123

issue of biosafety

, 127–128

issue of biosecurity

, 128–129

potential benefits and ethical issues of

, 123–129

synthetic biology

, 120–121

synthetic biology regulation

, 130–131

ProPublica

scrutiny of COMPAS tool

, 29

study COMPAS

, 39–40

Propulsion systems

, 162–163

Proto-centaur hybrids

, 184

Pseudonymization

, 64

Psychological health in HRC

, 73–74

Psychological support mechanisms

, 74

Psychopathy Checklist-Revised (PCL-R)

, 37–38

Quantitative Input Influence (QII)

, 45

Racial bias

, 34

Radiation astronauts

, 218–219

Radiation risks

, 219

Random Forest

classifier

, 28–29

model

, 43

Rat neonates

, 220

Rational discourse

, 108

Realism

, 61–62

Recidivism risk assessment instruments

, 35–39

Recombinant DNA technology

, 122

Reliability of ML systems

, 57–59

consequences of system failures

, 58

criticality of reliable ML

, 57

measures to enhance system reliability

, 58–59

Reproduction in space, historical perspectives on

, 216–217

Reproductive bioastronautics

, 225

Reproductive bioethics framework for space

, 223–225

Reproductive technologies

, 216, 225

Responsibility

, 10, 12–13

Responsibility gap concept

, 13

Risk

, 171–174

communication

, 224

of personal data misuse

, 63

Risk-Need-Responsivity model (RNR model)

, 36–38

Robot Ethics Charter

, 11

Robotics

, 165–166

Robots

, 143–144

Robust access control mechanisms

, 63

Rocketry

, 162–163

Rossum’s Universal Robots (R. U. R.)

, 137–138

Royal Academy of Engineering

, 120–121

Safety

, 9–10

Satellites and communications systems

, 162–163

Science and technology studies (STS)

, 32

Second wave of synthetic biology

, 122

Sexually transmitted infections

, 221–222

SHapley Additive exPlanations (SHAP)

, 45

Simulated liminality, unfamiliar futures and beneficial monsters in

, 185–194

Situation

, 109

Skeptical complex, tensions within

, 166–168

Skepticism

, 160–161, 171–172

Smartphone-based gamified job design

, 64–65

Social construction of reality (SCR)

, 115

Socrates, legacy of

, 98–102

Socratic approach

, 102

“Socratic hybrid” approach

, 100

Sophisms

, 91–92

Sophists

, 91–93

Space

, 4, 204–205

expansion

, 163

historical perspectives on reproduction in

, 216–217

human enhancement and type of space mission and rationale

, 203–205

human enhancement and vulnerable people in

, 209–211

potential benefits of using ectogenesis for space settlements

, 222–223

radiation

, 218–219

reproductive bioethics framework for

, 223–225

space-based Earth monitoring technologies

, 166

Space exploration

, 202–203

and utilization

, 180

Space skepticism

, 164, 169

partial merger of space skepticism with political activism

, 168–171

Space technologies

, 2–3, 162–163

partial merger of space skepticism with political activism

, 168–171

setting up problem

, 160–162

targeting of technologies of anthropocene

, 162–166

tensions within skeptical complex

, 166–168

timeliness and risk

, 171–174

Speech recognition models

, 33

State agencies

, 209–210

Static-99 Revised (Static-99(R))

, 38–39

Stereotyping

, 32

Super intelligence

, 18–19, 87

Super-intelligent AI

, 19–20, 22, 88

Super-intelligent artificial systems

, 18–19

Superior Second Law

, 17

Synthetic biologists

, 123–124

Synthetic biology

, 119–121, 129

regulation

, 130–131

synthetic biology 1.0

, 122

Synthetic genomics

, 124–125, 129

Synthetic Minority Over-sampling Technique (SMOTE)

, 45

Synthia

, 120, 122–123

Systems

consequences of system failures

, 58

theory

, 107

Technical Construction of Reality (TCR)

, 105–106

Technik-Lebenswelt

, 105–106

Techno-constructionism concept

, 105–106, 111

Technological construction of reality (TCR)

, 111

Technological development

, 5

Technological phenomenon

, 2, 115

Technological sectors

, 4–5

Technology

, 1–3, 105–106

Lebenswelt and

, 110–114

Teleological claim

, 164, 168

Temporalization

, 164

Tensions within skeptical complex

, 166–168

Terrestrial technology

, 173–174

Tetris

, 84

Theme

, 111

Timeliness

, 171–174

“Top-down approach”

, 98–100

Toxic Substances Control Act, The

, 130–131

Transfer learning technique

, 53

Transparency

in AI systems

, 32

challenges to achieving

, 56

imperative of

, 55–56

in ML systems

, 55–57

strategies for enhancing

, 56–57

“Transparency by design” concept

, 55–56

Trust

, 15

Turing test of ‘machine intelligence’

, 138

Turing’s universal machine

, 138

Ultra-violet radiation (UV radiation)

, 218–219

US National Research Council

, 124–125

User-centric design

, 57

Virtual reality (VR)

, 52

input devices

, 62–63

Vulnerable group

, 208, 211

Vulnerable people in space, human enhancement and

, 209–211

Vulnerable people on Earth, human enhancement and

, 205–209

War

, 160

Wasserstein Generative Adversarial Networks (WGANs)

, 44

Women

, 206–207

Women’s bodies as “problem”, institutional sexism and positioning of

, 216–217

Workplace, dehumanization concerns in

, 75

Workshop participants

, 188

Xenobots

, 152

Zeroth Law

, 9–11, 15–16, 18