Human-Centered Machine Learning: Harnessing Visualization and Interactivity for Unlocking Black-Boxes in AI

Human-Centered Machine Learning:
Harnessing Visualization and Interactivity
for Unlocking Black-Boxes in AI
DenisParra,AssistantProfessor
CS Department
Schoolof Engineering
PontificiaUniversidadCatólicadeChile
IMT,30 de Mayode2018

Presents …
• Assistant Professor DCC PUC
• Teaching
– Undergraduate:
• IIC 1005 Exploratorio del Major de Computación
• IIC 2026 Visualización de Información
– Graduate:
• IIC 3633 Sistemas Recomendadores
– Magister MPGI(Mineríade Datos),DiplomadoBig Data (Visualización)
• Research: SocVis Lab (http://socvis.ing.puc.cl)
– Machine Learningapplications (RecSys),informationvisualization,
informationretrieval,visual analytics
– 5 Master and 2 PhD students
– 3 undergraduatestudents
D.Parra ~ IMT PUCChile6/7/18 1

We are living incredible days…
• Technology is showing results which resemble
science fiction…
6/7/18 D.Parra ~ IMT PUCChile 2

Recognizing mental state from fMRI

Natural Language Processing
• IBM Watson beats humans in Jeopardy. << ... With
all of its processing CPU power, Watson can scan
two million pages of data in three seconds.>>E.
Nyberg, CMU professor
• Implications: Applications in Health domain.
http://www.aaai.org/Magazine/Watson/watson.php
Chile shares its largest frontier with this country …

Self-Driving Cars

Music Generation with Style
• Deep learningdriven jazz generation
• https://github.com/jisungk/deepjazz
• https://soundcloud.com/deepjazz-ai

Mastering Go

AI for incorporating style in images
https://github.com/luanfujun
/deep-painterly-
harmonization

But there are some problems

AI for automatic decision making…
https://www.fastcompany.com/40557688/this-plan-for-an-ai-based-direct-democracy-
outsources-votes-to-a-predictive-algorithm

Some voices call for calm…
https://medium.com/@mijordan3/artificial-intelligence-the-revolution-hasnt-happened-yet-
5e1d5812e1e7
Thus, just as humans built buildings and bridges
before there was civil engineering, humans are
proceeding with the buildingof societal-scale,
inference-and-decision-making systems that
involve machines, humans and the environment.
Just as early buildings and bridges sometimes fell
to the ground — in unforeseenways and with
tragic consequences — many of our early societal-
scale inference-and-decision-making systems are
already exposing serious conceptual flaws.

Part II
• What happened in May 25th 2018
• Which role can take Information Visualization and
Interaction in AI ?

So, What happened in May 25th, 2018 ?
• The EU General Data Protection Regulation
(GDPR) becomes enforceable.

And why do we care in this room ?
• The GDPR not only applies to organisations
located within the EU but it will also apply to
organisations located outside of the EU if they
offer goods or services to, or monitor the behaviour
of, EU data subjects.
• It applies to all companies processing and
holding the personal data of data subjects
residing in the European Union, regardless of the
company’s location.

Human Interpretability in ML
D.Parra ~ IMT PUCChile
• https://arxiv.org/abs/1606.08813
6/7/18 15

Which is the effect on my current practice ?
Right to explanation
• Article 15 “Right of access by the data subject”
• Article 22 “Automated individual decision-
making, including profiling”
• Recital 71 (linked to art. 22)

Article 15

Article 15
<<The data subject shall have the right to
obtain … access to the personal
data … [information of] the existence of
automated decision-making, including
profiling, referred to in Article 22(1) and (4)
and, at least in those cases, meaningful
information about the logic involved … >>
6/7/18 18

Article 22

Article 22
I
<<The data subject shall have the right not to
be subject to a decision based solely on
automated processing, including profiling,
which produces legal effects concerning him
or her or similarly significantly affects him or
her.… >>
6/7/18 20

Article 22
II
<<Decisions referred to in paragraph 2 shall
not be based on special categories of personal
data referred to in Article 9(1), >>
Processing of personal data revealing racial
or ethnic origin, political opinions,
religious or philosophical beliefs … (cont.)
6/7/18 21

Article 22
II
…or trade union membership, and the
processing of genetic data, biometric data for
the purpose of uniquely identifying a natural
person, data concerning health or data
concerning a natural person's sex life or sexual
orientation shall be prohibited
6/7/18 22

Recital 71

Recital 71
In order to ensure fair and transparent processing
in respect of the data subject, taking into account
the specific circumstances and context in which
the personal data are processed, the controller
should use appropriate mathematical or statistical
procedures for the profiling …
6/7/18 24

Other Initiatives (2018)
This bill would require the creation of a
task force that provides
recommendations on how information
on agency automated decision systems
may be shared with the public and how
agencies may address instances where
people are harmed by agency
automated decision systems.

ML and GDPR
• How do we explain Machine Learning models?
• From Decision Trees to Deep Neural Networks
Explainable decision model, explicit
variables, not very accurate
Black-box decision model,
latent variables, accurate
6/7/18 26

Challenges
• Are there methods to explain models?
– Can we create methods to help us explain decisions
made by complex models such as DNN ?
• Can visualization & interaction help in this issue?

IEEE Vis 2016

Detail

IEEE VIS 2017

IEEE 2017 VAST Best Paper
• Visualizing Dataflow Graphs of Deep Learning
Models in TensorFlow
Authors: Kanit Wongsuphasawat, Daniel Smilkov, James Wexler, Jimbo Wilson,
Dandelion Mané, Doug Fritz, Dilip Krishnan, Fernanda B. Viégas, and Martin
Wattenberg

How do RNNs work?

Do CNNs learn hierarchies ?

Symposium: Visual Data Science + ML

UBER Visualization and Machine Learning

Workshop on Explainable ML

Workshop on Explainable ML
DARPA is funding
Explainable AI
6/7/18 37

New Journals & Conferences
• Distill.pub
• FAT conference

Distill.pub

Distill.pub
Ejemplo: t-SNE
https://distill.pub/2016/misread-tsne/

https://fatconference.org/
• The FAT* Conference 2018 is a two-day event that
brings together researchers and practitioners
interested in fairness, accountability, and
transparency in socio-technical systems.

My Previous work

Visual & interactive RecSys interfaces
• IUI 2013 IUI 2014 UMAP 2016
• IUI 2018
6/7/18 43

Moodplay
http://moodplay.pythonanywhere.com

Topic Models
• Very popular models to analyze collections of text.
• They allow to summarize large corpuses by finding
topics in unsupervised fashion.

Topic Models
• Very popular models to analyze collections of text.
• They allow to summarize large corpuses by finding
topics in unsupervised fashion.
But they also:
- Report topics with little sense,
- redundants, or
- Where vocabulary with unbiased importance to frequent words
Does not work well with short texts

ESIDA – IUI 2018

Research (M.F. Sepúlveda)
• Development of interfaces with interaction which
allows people to deal with unsupervised models,
using a Human-in-the-loop for semi-supervision.

IEEE VIS 2017 – Panel ML & Vis ?

Conclusion
• Deep Neural Networks have produced tremendous
progresses in several fields in the latest years (computer
vision, NLP, recommender systems, etc.)
• Technology is not innocuous: depending on the data
used and the characteristics of the methods, can have
several implications in our societies, not always
positive.
• Foreseeing the impact of ML and AI, regulations are
requiring transparency, explainability, inspectability
and other characteristics which need further research.

Research Opportunities
• Explaining Machine Learning (classification,
prediction, clustering, etc.)
• www.distill.pub
• Visualization & Interaction for Explainable ML
• FAT: Fairness, Accountability, Transparency
(https://fatconference.org/)

• Effect of ML models on Social Issues
– Filter Bubble/Echo Chambers
– Does Facebook influenced the results of presidential
elections ?
Facebook newsfeed recommendation model
6/7/18 56

• New Millenium Institute for Foundational Research
on Data (IMFD)
– Lidera Profesor Marcelo Arenas, DCC PUC Chile
– Investigadores de PUC, UChile, USM, UdeC
– Áreas: Computación, Estadística, Matemáticas,
Sociología, Ciencia Política, Comunicaciones
(Periodismo)

References
• Goodman, B., & Flaxman, S. (2016). EU regulations
on algorithmic decision-making and a “right to
explanation”. In ICML workshop on human
interpretability in machine learning (WHI 2016),
New York, NY. http://arxiv. org/abs/1606.08813
v1.
• Edwards, L., & Veale, M. (2017). Slave to the
Algorithm? Why a ‘Right to Explanation’ is
Probably Not the Remedy You are Looking for.
Duke Law & Technology Review.

Human-Centered Machine Learning: Harnessing Visualization and Interactivity for Unlocking Black-Boxes in AI

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