I work at ValueFirst Digital Media Private Ltd. I am a Product Marketer in the Surbo Team. Surbo is Chatbot Generator Platform owned by Value First. ...
Full BioI work at ValueFirst Digital Media Private Ltd. I am a Product Marketer in the Surbo Team. Surbo is Chatbot Generator Platform owned by Value First.
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Artificial intelligence could help humans win arguments
The ability to argue, to express our reasoning to others, is
one of the defining features of what it is to be human.
Argument and debate form the cornerstones of civilized
society and intellectual life. Processes of argumentation run our governments,
structure scientific endeavor and frame religious belief. So should we worry
that new advances in artificial intelligence are taking steps towards equipping
computers with these skills?
As technology reshapes our lives, we are all getting used to
new ways of working and new ways of interacting. Millennials have known nothing
else.
Governments and judiciaries are waking up to the potential
offered by technology for engaging citizens in democratic and legal processes.
Some politicians, individually, are more ahead of the game in understanding the
enormous role that social media plays in election processes. But there are
profound challenges.
One is nicely set out by Upworthy chief executive Eli
Pariser in his TED Talk. In it he explains how we are starting to live in
â??filter bubblesâ??: what you see when you search a given term on Google is not
necessarily the same as what I see when I search the same term.
Media organizations from Fox News to, most recently, the
BBC, are personalizing content, with ID and login being used to select which
stories are featured most prominently. The result is that we risk locking
ourselves into echo chambers of like-minded individuals while our arguments
become more one-sided, less balanced and we have less understanding of other
viewpoints.
Another concern is the way in which news and information,
though ever more voluminous, is becoming ever less reliable â?? accusations and
counter-accusations of â??fake newsâ?? are now commonplace.
In the face of such challenges, skills of critical thinking
are more vital now than they have ever been â?? the ability to judge and assess
evidence quickly and efficiently, to step outside our echo chamber and think
about things from alternative points of view, to integrate information, often
in teams, balance arguments on either side and reach robust, defensible
conclusions. These are the skills of argument that have been the subject of
academic research in philosophy for more than 2,000 years, since Aristotle.
The Centre for Argument Technology (ARG-tech) at the
University of Dundee is all about taking and extending theories from
philosophy, linguistics and psychology that tell us about how humans argue, how
they disagree, and how they reach consensus â?? and making those theories a
starting point for building artificial intelligence tools that model, recognize,
teach and even take part in human arguments.
One of the challenges for modern research in the area has been getting enough data. AI techniques such as deep learning require vast amounts of data, carefully reviewed examples that can help to build robust algorithms.
But getting such data is really tough: it takes highly
trained analysts hours of painstaking work to tease apart the way in which
arguments have been put together from just a few minutes of discourse.
More than 10 years ago, ARG-tech turned to the BBC Radio 4
program Moral Maze as an example of â??gold standardâ?? debate: rigorous, tight
argument on emotive, topical issues, with careful and measured moderation.
Enormously valuable, that data fed a program of empirically grounded research
into argument technology.
Working with such demanding data has meant that everything
from philosophical theory to large-scale data infrastructure has been put to
the test. In October, we ran a pilot with BBC Radioâ??s religion and ethics
department to deploy two types of new argument technology.
The first was a set of â??analyticsâ??. We started by building
an enormous map of each Moral Maze debate, comprising thousands of individual
utterances and thousands more connections between the contents of all of those
utterances. Each map was then translated into a series of infographics, using
algorithms to determine the most central themes (using something similar to
Googleâ??s PageRank algorithm). We automatically identified the most divisive
issues and where participants stood, as well as the moments in the debate when conflict
reached boiling point, how well-supported arguments were, and so on.
The result, at bbc.arg.tech in conjunction with the Moral
Maze presents, for the first time, an evidence-based way of understanding what
really happens in a debate.
The second was a tool called â??debaterâ??, which allows you to
take on the role of the chair of the Moral Maze and run your own version. It
takes the arguments offered by each participant and allows you to navigate
them, following your own nose for a good argument.
Both aspects aim to offer insight and encourage
better-quality, more reflective arguing. One the one hand, the work allows
summaries of how to improve skills of arguing, driven by evidence in the data
of what actually works.
On the other is the opportunity to teach those skills
explicitly: a Test Your Argument prototype deployed on the BBC Taster site uses
examples from the Moral Maze to explore a small number of arguing skills and
lets you pit your wits directly against the machine.
Ultimately, the goal is not to build a machine that can beat
us at an argument. Much more exciting is the potential to have AI software
contribute to human discussion â?? recognizing types of arguments, critiquing
them, offering alternative views and probing reasons are all things that are
now within the reach of AI.
And it is here that the real value lies â?? having teams of arguers, some human, some machine, working together to deal with demanding, complex situations from intelligence analysis to business management.
Such collaborative, â??mixed-initiativeâ?? reasoning teams are
going to transform the way we think about interacting with AI â?? and hopefully
transform our collective reasoning abilities too.