Codes of ethics can be prescriptive (prescribe the do's and don'ts) or aspirational
(only specify ideal results). Ferguson et al. (2016) note that they are an important
tool for archivists, yet not always sufficient, especially not when there are conflicts
between rules and values.
Archival codes49 of ethics have a history. The first dates from 1955, from the Society
of American Archivists (SAA). It (SAA 1955) is fairly compact and states things like:
"The Archivist should endeavour to promote access to records to the fullest
extent consistent with the public interest, but he should carefully observe
any proper restrictions on the use of records".
Similar statements come from the Universal Declaration on Archives
(ICA-DL 2011):
"Archives are made accessible to everyone, while respecting the pertinent
laws and the rights of individuals, creators, owners and users".
"The Archivist should respond courteously and with a spirit of helpfulness
to reference requests."
"The Archivist should not profit from any commercial exploitation of
the records in his custody."
Later (SAA 1992) it includes:
"It is not sufficient for archivists to hold and preserve materials: they also
facilitate the use of their collections and make them known."
This amounts to the preservation, use and publicity aspects of the archive. It also
contains:
"Archivists endeavour to inform users of parallel research by others using
the same materials, and, if the individuals concerned agree, supply each
name to the other party."
This refers to a dilemma I have discussed.
The final commentary of the code states something about potential conflicts:
"When there are apparent conflicts between such goals and either the
policies of some institutions or the practices of some archivists, all
interested parties should refer to this code of ethics and the judgment of
experienced archivists."
The most recent version (SAA 2012) features additional core values, which represent
what the archivists believe while the code itself represents a framework for the
archivists' behavior. This division is intuitive and could be a way to solve some ethical
dilemmas, for example by a utilitarian analysis weighing in more factors. For access
it expresses the value that it is essential in personal, academic, business and
government settings, and use of records should be welcomed. Later in the code of
ethics itself this value is translated into "minimize restrictions and maximize ease of
access".
Ethical codes, especially when they have consequences when misbehaving, cause
fewer discipline problems among members (Kizza, 2016, p. 50). However, some
codes of conduct can be non-committal. Morris50 calls for an enforceable code of
ethics, just like legal and medical professions are governed by codes of ethics which
carry the force of law. Violations would then be subject to sanctions including loss of
license and civil and criminal liabilities. Formalizing ethical codes though, has one
main purpose: to formalize how humans should behave, in this case in the archival
profession. I call this the intended archivist; how he is supposed to think, feel and
act professionally based on human values and human behavior. By formalizing it in a
code it becomes transparent and can be communicated to peers, users, donor
organisations and the general public.
(4) The Ethics of Algorithms
For algorithms, ethical analysis has only started recently resulting in the
multidisciplinary field of ethics of algorithms (see for pointers: Lichocki et al., 2011;
van Otterlo, 2013,2014a,2014b,2016a; Medina, 2015; Mittelstadt et al., 2016).
People often associate with algorithms properties such as infallible, exact, and
especially: objective. Because computer-based algorithms are based on logic and
statistics people tend to think that because of that algorithms are objective and fair,
since they can compute the best answers given the data. While some of this may be
true, in general algorithms are far from objective: they are heavily biased (Bozdag,
2013; van Otterlo, 2013). Consider for example51 (part of) a simple algorithm for a
bank, specifying that "IF sex female AND age 60 THEN decision no-life-
insurance-policy". Now this algorithm is perfectly mathematical, and exact, and it
thoroughly computes from personal data whether somebody is eligible for a life
insurance policy. However, from a human point of view, it is far from "objective",
or "fair" since it discriminates against women above 60 years old. Its decisions are
biased and it discriminates, in plain sight. To make things worse, we can also imagine
a second algorithm which is specified as "IF f(sex) g(age) 3.78 THEN decision
no-life-insurance-policy", and let us assume it makes exactly the same decisions as
the first. A problem here is that this algorithm discriminates too, but it is hard to see
from its description because we do not know what the functions f() and g() do, and
also not why there is a threshold of exactly 3.78. Maybe these aspects have been
learned from data which would require us to have a look at the data and learning
process to form an opinion about the algorithm's objectiveness. In general,
algorithms are biased in many ways (Bozdag, 2013), for example by the data, by
learning procedures, by programmers who make choices, by technological
constraints and many other reasons. This immediately requires us to form an
opinion about algorithms and whether they do the right thing, which again brings us
back to ethical reasoning.
Characterizing the ethics of algorithms is hard since algorithms and potential
consequences are so diverse, and situations may change over time. Mittelstadt et al.
(2016) define concerns about how algorithms transform data into decisions, which
are then coupled with typical ethical issues. The core operations of an algorithm are:
1) it turns data into evidence which can be a probabilistic prediction, a yes-no
decision, or some other conclusion, and 2) it uses the evidence to trigger and motivate
an action based on the data. For example, an algorithm for bank loans could take
personal data of someone and produce a credit-score of 12, which then could trigger
an action to approve a particular mortgage. For the first step three general concerns
archives in liquid times
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martijn van otterlo from intended archivists to intentional algivists.
ethical codes for humans and machines in the archives
49 Many other related codes exist, for example by the Dutch royal association for archivists (KVAN)(1) and the
professional charter for librarians in public libraries (PL 1993)(2), and codes by the American library
organization (ALA)(3), the International Federation of Library Associations and Institutions (IFLA)(4) and
the International Council of Museums (ICOM)(5) code of ethics for museums. Although libraries do have
different activities, core values are shared with archivists, which can be seen in the similarities with library
values concerning access. Occasionally separate codes are made with respect to specific aspects such as
privacy, for example as was done recently by IFLA in 2015 (6). See: (1) http://kvan.nl/images/PDF/
Beroepscode_voor_Archivarissen.pdf; (2) http://www.ifla.org/files/assets/faife/codesofethics/netherlands.
pdf; (3) http://www.ala.org/advocacy/proethics/codeofethics/codeethics; (4) http://www.ifla.org/news/
ifla-code-of-ethics-for-librarians-and-other-information-workers-full-version; (5) http://icom.museum/
fileadmin/user_upload/pdf/Codes/code_ethics2013_eng.pdf; (6) https://www.ifla.org/node/9803
50 http://slanynews.blogspot.nl/2010/09/enforceable-code-of-ethics-why.html
51 Birkbak and Carlsen (2016) elegantly show in a toy experiment how bias that is explicitly put in (the code
of) a ranking algorithm causes different results, exemplifying how implementation choices change
algorithm outcomes. As bias, they use intuitive operationalizations of the company mottos of Google,
Facebook and Twitter.
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