Hello everyone, my name is Niall Docherty, and I’m a Critical Theorist based at Microsoft Research within the Social Media Collective.
My co-author is Asia Biega, a computer scientist based at the Max Planck Institute for Security and Privacy.
This presentation will outline the key arguments and findings of our research on re-politicizing digital well-being.
Concerns surrounding digital well-being have grown in recent years, and much of this debate
is encapsulated in the notion of time well spent.
Here, users are encouraged to manage their time on platforms in a productive manner,
and conscious engagement is presented as the key to the digital good life.
However, our paper argues that this view of digital well-being is empirically and ideologically
reductive, as it fails to take into account the social, cultural, environmental, and material
circumstances that condition well-being in different sociotechnical contexts.
Well-being is a relative concept in two related ways.
First, the 'well' in well-being mobilizes normative judgements about how humans should best live their lives.
Second, the 'being' in well-being requires an ontological definition of what the human being actually is.
Well-being is thus always a normative statement tied to the time, place, and culture of its articulation.
Accordingly, our paper argues that HCI practitioners ought to make the normative stakes and ethical
implications of digital well-being explicit at every stage of the design process.
We further highlight the necessity of this by critically examining one readily available
present-day marker: user engagement metrics.
The idea of 'time-well-spent' on a platform, and, in particular, the ideas of connection and disconnection
made us wonder how platforms may attempt to automatically measure these concepts.
This brought us to thinking about user engagement metrics, which broadly aim at quantifying
the quality of user experience on a platform.
A question that arises is whether user engagement can be an adequate and sufficient proxy for
well-being?
And the short answer is: no.
In the paper, we ground this argument in a comparison between measures of user engagement
and diagnostic dimensions of digital addiction as formalized in Young's Internet Addiction Questionnaire.
We make two key observations.
First, we point out that only two out of eight dimensions of digital addiction are likely
to incur observable changes in engagement metrics.
And second, we argue that most other diagnostic dimensions of digital addiction cannot be
captured by behaviorist metrics of on-platform behavior as they relate to aspects of a person’s
life that are typically not accessible to the platform.
A website indeed would rarely know about lost job opportunities, emotions a person feels
when not using the platform, or a user's personal relationships.
Overall, we show that similar observational patterns in user engagement can be a sign
of both well-being increasing and decreasing behaviours.
And an automated analysis might be impossible without understanding a person's socio-material,
emotional, and cognitive circumstances.
But creating models that account for user circumstances comes at a cost.
It might require us to resort invasive designs and extensive collection of sensitive user data.
Allowing service providers to design in this way invites a refection on the downstream
negative consequences for privacy, user autonomy, and the power balance between users and platforms.
There are other design approaches we might consider.
Instead of comprehensively modeling digital well-being, we might circumstantially manage
negative externalities.
For instance, we could be reducing user exposure to content typically considered harmful.
Instead of making assumptions or inferences about the well-being needs of individuals
and user populations, we might actively seek their input through value-sensitive and participatory approaches.
Considering fairness in all facets of our systems, will allow us to improve well-being
as understood by structural accounts.
Here, we can draw inspiration from a variety of approaches, from algorithmic fairness
to equity-focused teaching.
Finally, we should grapple with the question of whether it's appropriate to design for
well-being at all, or whether any effort will necessarily be a
“computationally tractable transformation of a problem”?
Measuring relative depreciations of well-being in digital contexts can provide an opportunity
to discuss the psychological impacts that intersecting inequalities and oppression has on users.
Doing so would treat the psychological issues manifest through specified forms of user engagement
as social issues.
This is opposed to them simply being treated as personal behaviors separate from the material
conditions that support and sustain them.
We argue that declining experiences of user well-being ought to be understood as symptoms
of operative inequalities in the world, such as those emergent in contemporary structures
of neoliberal capitalism.
Moreover, digital distress can also be viewed as symptomatic of operative systemic prejudices,
such as those associated with classism, racism, and misogyny.
We have shown how measuring the impact of these inequalities on user is beyond the capability
of user engagement metrics alone.
However, failing to recognize the limits of user engagements as a proxy for well-being,
and without advocating the need for them to be supplemented by other well-being metrics,
has the effect of rendering these salient social factors
as unimportant.
This is not only empirically limiting, but is an ideological gesture.
Ignoring the social, cultural, and economic inequalities that produce differences in user
well-being is as much to say that these inequalities do not matter.
As a result, the political need to ameliorate these inequalities is shut down.
This enables existing power structures to remain in place unchecked, and the opportunity
to link digital well-being with wider social justice issues is lost.
If HCI experts wish to confront these issues head on, it is crucial to incorporate the
structural, social, and systemic determinants of digital well-being in its conceptualization,
measurement, and design.
Thank you for listening!