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How language can be used to both identify and obscure

Like the northeastern girl, there are thousands of girls scattered throughout the tenement slums, vacancies in beds in a room, behind the shop counters working to the point of exhaustion. They don’t realize how easily substitutable they are and that they could just as soon drop off the face of the earth. Few protest and as far as I know they never complain since they don’t know to whom. Does this whom exist?

The Hour of the Star by Clarice Lispector (translated by Benjamin Moser)

(Observing from the) background

I have a strange, voyeuristic fascination with reading the responses to tweets and other forms…


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Photo by Brett Jordan on Unsplash

An ethical framework for natural language applications

Note: Although this article is written as a five-part series, it is not necessary to read each part in order, nor is it necessary to read all parts, as each part has been written as a standalone piece.

Introduction

In Part III of this series (linked below), inspired by a quote from Deep Learning with PyTorch (further below), to build toward propositions for (1) verified humans on social media platforms and (2) transparency regarding the use of language models to generate text, I discussed the possibility of a machine forming a thesis by exploring both mechanical desires and algorithmically generated worldviews.


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Photo by Mark König on Unsplash

An Argument for Verified Humans (Part III)

Note: Although this article is written as a five-part series, it is not necessary to read each part in order, nor is it necessary to read all parts, as each part has been written as a standalone piece.

Introduction

In Part II of this series (linked below), inspired by a quote from a guidebook called Deep Learning with PyTorch (further below), I explored the changing nature of communication with human language to build toward propositions for (1) verified humans on social media platforms and (2) transparency regarding the use of language models to generate text.

In this article, to answer the…


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Photo by Priscilla Du Preez on Unsplash

An Argument for Verified Humans (Part II)

Note: Although this article is written as a five-part series, it is not necessary to read each part in order, nor is it necessary to read all parts, as each part has been written as a standalone piece.

Introduction

In Part I of this series (linked below), inspired by a quote from a guidebook called Deep Learning with PyTorch (further below), I embarked on a journey toward propositions for (1) verified humans on social media platforms and (2) transparency regarding the use of language models to generate text by discussing the unimportance of the semantic classification of the actions and capabilities…


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Photo by Marat Gilyadzinov on Unsplash (Author’s note: In either Autumn or Winter of his Seasons Quartet, Karl Ove Knausgaard supposes the hypothetical life of the human brain, removed from the confines of the skull, as an independent organism; he suggests that the brain would be a sea creature not unlike a jellyfish, with nerves like tentacles floating behind it. I liked the imagery evoked by supposing this strange yet familiar creature, as well as the implied importance of anatomy, for if our brains were not given our bodies, what good would they be? — and so is it the body that defines want, and the brain a servant of the body? — and so what can we make of a neural network?)

An Argument for Verified Humans (Part I)

Note: Although this article is written as a five-part series, it is not necessary to read each part in order, nor is it necessary to read all parts, as each part has been written as a standalone piece.

Introduction

As I read, I often get lost in the text, my thoughts diverging from the author’s words toward something related yet different. This process seems almost like a conversation between the author and me, with a person’s words provoking my response. At times, I enjoy this aspect of reading, but more often, it is quite distracting.

Still, if I find the thoughts…


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Photo by Possessed Photography on Unsplash

Artificial Intelligence, Machine Intelligence, Opinion

What do we question when we ask if machines can think?

An interesting concept from literary theory states that if a reader wants to make sense of a text, then he will find an interpretation of that text that is consistent with his own world view, or perhaps more precisely, with his view of the world he supposes the text to concern. Oftentimes, to fulfill such a desire requires the reader to fill gaps in his own knowledge, as well as gaps in the logic or rhetoric of the writer by reading between the lines.


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Photo by Markus Winkler on Unsplash

What analogies can tell us about our language and our algorithms

The Natural Language Processing (NLP) group at Stanford University made publicly available the list of papers from their CS 384 seminar on Ethics and Social Issues in Natural Language Processing, and so I have been on a bit of a reading binge trying to learn more about this fascinating and important topic.

In this article, I want to explore the use of analogies for identifying biases in word embeddings by focusing on two papers on the topic: Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016) [1] and Fair Is Better than Sensational: Man Is…


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Photo by Mikael Kristenson on Unsplash

Opinion

Is a formal education better than the alternatives?

As machine learning becomes more ubiquitous and its software packages become easier to use, it is natural and desirable that the low-level technical details are abstracted away and hidden from the practitioner. However, this brings with it the danger that a practitioner becomes unaware of the design decisions and, hence, the limits of machine learning algorithms. [1]

In this article, I want to discuss my experience in a formal degree program in analytics and draw comparisons with an autodidactic approach (here, defined to include books, projects, YouTube tutorials, MOOCs, and any other à la carte learning that cannot be summed…


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Photo by Alexandra on Unsplash

The inherent difficulty of balancing algorithms and design

Language is always situated, i.e., it is uttered in a specific situation at a particular place and time, and by an individual speaker with all the characteristics outlined above. All of these factors can therefore leave an imprint on the utterance. [1]

I have a bit of an obsession with language and communication that is difficult to summarize with a pithy list, but I will try: At any given time, I am reading between 5 and 25 books, and I am learning between 1 and 4 languages, with varying degrees of success; I am growing a note of phrases I…


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Photo by Kevin Horvat on Unsplash

How a changing technical environment has shifted power away from decision-makers

Future Data 2020

Earlier this week, I (virtually) attended Future Data 2020, a conference about the next generation of data systems. During the conference, I watched an interesting talk given by Tristan Handy, founder and CEO of Fishtown Analytics, called The Modern Data Stack: Past, Present, and Future. During the talk, Tristan discussed a so-called Cambrian explosion of data products built upon data warehouses, such as Amazon Redshift, between 2012 and 2016, as well as his opinion that we are on the precipice of a similar paradigm shift, which he referred to as “the second Cambrian explosion.”

Tristan’s perspective on the modern data…

Danielle Boccelli

MSc Analytics ’16 @ Georgia Tech | BSc ChemEng ’15 @ Drexel U | @danielleboccell

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