On the Efficiency of Ethics as a Governing Tool for Artificial Intelligence

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ON THE EFFICIENCY OF ETHICS AS A GOVERNING TOOL FOR

ARTIFICIAL INTELLIGENCE

A CRITICAL COMPARISON BETWEEN AI ETHICS AND BIOETHICS

PONTIFICAL CATHOLIC UNIVERSITY OF RIO GRANDE DO SUL

Nicholas Kluge Corrêa

Graduate Program in Philosophy

Pontifical Catholic University of Rio Grande do Sul

nicholas@airespucrs.org

Nythamar De Oliveira

Graduate Program in Philosophy

Pontifical Catholic University of Rio Grande do Sul

nythamar.oliveira@pucrs.br

Diogo Massmann

Graduate Program in Philosophy

Pontifical Catholic University of Rio Grande do Sul

diogo.massmann@edu.pucrs.br

October 26, 2022

ABSTRACT

The 4th Industrial Revolution is the culmination of the digital age. Nowadays, technologies such

as robotics, nanotechnology, genetics, and artificial intelligence promise to transform our world

and the way we live. Artificial Intelligence Ethics and Safety is an emerging research field that has

been gaining popularity in recent years. Several private, public and non-governmental organizations

have published guidelines proposing ethical principles for regulating the use and development of

autonomous intelligent systems. Meta-analyses of the AI Ethics research field point to convergence

on certain principles that supposedly govern the AI industry. However, little is known about the

effectiveness of this form of “Ethics.” In this paper, we would like to conduct a critical analysis of

the current state of AI Ethics and suggest that this form of governance based on principled ethical

guidelines is not sufficient to norm the AI industry and its developers. We believe that drastic changes

are necessary, both in the training processes of professionals in the fields related to the development

of software and intelligent systems and in the increased regulation of these professionals and their

industry. To this end, we suggest that law should benefit from recent contributions from bioethics, to

make the contributions of AI ethics to governance explicit in legal terms.

Keywords artificial intelligence ethics · ethical guidelines · governance · bioethics · regulation

Introduction

Intelligent autonomous systems are increasingly becoming part of our society. Tasks and work previously performed by

us are delegated to systems embedded with artificial intelligence (AI). The so-called 4th Industrial Revolution is the

culmination of the digital age, where technologies such as robotics, nanotechnology, genetics, and artificial intelligence

promise to transform our world and how we live. And, currently, the most accessible and massively used of these

technologies is AI.

When we talk about AI regulation, our problems start with the question "what is AI?" A conclusive definition of AI,

as recommended by international agencies like the United Nations Educational, Scientific and Cultural Organization

Graduate Program in Philosophy

PUC-RS

(Unesco),

is currently an impossibility. Such a definition would change periodically as new technologies and technical

resources allow innovations in the AI concept itself.

However, if we postulate that human/biological intelligence is what enables the execution of tasks that involve visual

perception, speech recognition, decision-making, and natural language processing (among many others), AI would be

understood as a computational system that integrates models and algorithms capable of coping with the complexity of

such tasks.

These models and algorithms are what people refer to when speaking about AI. A field that as its current paradigm

presents methodologies like machine learning, deep learning, reinforcement learning, and genetic algorithms, among

many others [34]. Taking a more philosophical/cognitive science approach, following John Searle [36], one can still

make the distinction between weak AI2 and strong AI3. Over time, the definition of "strong AI" has come to refer to

terms like “human-level AI”4 or “Artificial General Intelligence” (AGI). 5

To illustrate the reach that such systems have, we can cite the examples below as some types of AI used by the Brazilian

public authorities:

•

The National Telecommunications Agency uses natural language models to identify standard consumer

behavior;

•

The National Land Transport Agency uses AI to predict the average daily flow of traffic on federal highways;

•

Bank of Brazil uses natural language models (chatbots) for customer service, CNNs for facial recognition;

•

Federal Savings Bank uses AI to predict fraudulent electronic transactions;

•

The Coordination for the Improvement of Higher Education Personnel uses AI to confirm the authorship of

publications and academic projects;

•

The Federal Police Department uses AI for facial recognition and natural language models for risk prediction

(e.g., fraud detection);

•

Brazilian Agricultural Research Company uses AI to predict the best vegetable to be grown in a crop and

image classification to detect diseases in crops;

•

The National Institute of Social Security uses AI to predict irregularities in the issuance of social benefits;

•

The Federal Supreme Court uses AI to categorize legal proceedings under general repercussions;

•

The Supreme Court of Justice uses AI to perform automatic scans for each appeal presented to the court,

cross-reference appeals with previous rulings (search for legal precedents), and generate recommendations for

Ministers.

And there are many more cases of application of this type of technology, not only by the public sector but by all sectors

that, in some way, interact with our society.

Given the transformative power of AI, it would be important for us to have a consensus on the norms and guidelines that

govern such technologies. The field of AI ethics and safety and (AI Safety and AI Ethics) are emerging research areas

that have gained popularity in recent years. Several private, public, and non-governmental organizations have published

guidelines that propose ethical principles to improve the regulation of autonomous intelligent systems [33] [1] [18] [19].

In this article, we will focus on the normative challenges and problems inherent in the "enforcement" of AI Ethics. As

much as this is a relatively new field of Applied Ethics, AI Ethics already has enough literature for meta-analyses of the

field to have been carried out [22] [20] [12] [9].

One of the results that we can observe in these meta-analyses is that there

is a convergence to a set of generic ethical principles (especially when AI Ethics is embroidered in a principled way):

Accountability/Liability, Beneficence/Non-Maleficence, Children & Adolescents Rights, Dignity/Human Rights, Diver-

sity/Inclusion/Pluralism/Accessibility, Freedom/Autonomy/Democratic Values/Technological Sovereignty, Human For-

mation/Education, Human-Centeredness/Alignment, Intellectual Property, Justice/Equity/Fairness/Non-discrimination,

Labor Rights, Open source/Fair Competition/Cooperation, Privacy, Reliability/Safety/Security/Trustworthiness, Sus-

tainability, Transparency/Explainability/Auditability, Truthfulness.

Recommendation on the Ethics of Artificial Intelligence. Available in

https://unesdoc.unesco.org/ark:/48223/

pf0000380455

2A type of artificial intelligence that is limited to a specific or narrow area.

An artificial intelligence that constructs mental abilities, thought processes, and functions that are impersonated from the human

brain.

4A type of artificial intelligence that can perform as well as a human being in any task.

5A type of artificial intelligence that can solve many problems (proficiently) and in a wide range of applications and domains.

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ONTHEEFFICIENCYOFETHICSASAGOVERNINGTOOLFORARTIFICIALINTELLIGENCEACRITICALCOMPARISONBETWEENAIETHICSANDBIOETHICSPONTIFICALCATHOLICUNIVERSITYOFRIOGRANDEDOSULNicholasKlugeCorrêaGraduatePrograminPhilosophyPontificalCatholicUniversityofRioGrandedoSulnicholas@airespucrs.orgNythamarDeOliveiraGraduateProgram...

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