̽��ֱ�� of Cambridge - Marcus Tomalin

Online hate speech could be contained like a computer virus, say researchers

fpjl2 — Tue, 17 Dec 2019 17:37:13 +0000

̽��ֱ��spread of hate speech via social media could be tackled using the same 'quarantine' approach deployed to combat malicious software, according to ̽��ֱ�� of Cambridge researchers.

Definitions of hate speech vary depending on nation, law and platform, and just blocking keywords is ineffectual: graphic descriptions of violence need not contain obvious ethnic slurs to constitute racist death threats, for example.

As such, hate speech is difficult to detect automatically. It has to be reported by those exposed to it, after the intended "psychological harm" is inflicted, with armies of moderators required to judge every case.

This is the new front line of an ancient debate: freedom of speech versus poisonous language.

Now, an engineer and a linguist have published a proposal in the journal Ethics and Information Technology that harnesses cyber security techniques to give control to those targeted, without resorting to censorship.

Cambridge language and machine learning experts are using databases of threats and violent insults to build algorithms that can provide a score for the likelihood of an online message containing forms of hate speech.

As these algorithms get refined, potential hate speech could be identified and "quarantined". Users would receive a warning alert with a "Hate O'Meter" – the hate speech severity score – the sender's name, and an option to view the content or delete unseen.

This approach is akin to spam and malware filters, and researchers from the 'Giving Voice to Digital Democracies' project believe it could dramatically reduce the amount of hate speech people are forced to experience. They are aiming to have a prototype ready in early 2020.

"Hate speech is a form of intentional online harm, like malware, and can therefore be handled by means of quarantining," said co-author and linguist Dr Stefanie Ullman. "In fact, a lot of hate speech is actually generated by software such as Twitter bots."

"Companies like Facebook, Twitter and Google generally respond reactively to hate speech," said co-author and engineer Dr Marcus Tomalin. "This may be okay for those who don't encounter it often. For others it's too little, too late."

"Many women and people from minority groups in the public eye receive anonymous hate speech for daring to have an online presence. We are seeing this deter people from entering or continuing in public life, often those from groups in need of greater representation," he said.

Former US Secretary of State Hillary Clinton recently told a UK audience that hate speech posed a "threat to democracies", in the wake of many women MPs citing online abuse as part of the reason they will no longer stand for election.

While in a Georgetown ̽��ֱ�� address, Facebook CEO Mark Zuckerberg spoke of "broad disagreements over what qualifies as hate" and argued: "we should err on the side of greater expression".

̽��ֱ��researchers say their proposal is not a magic bullet, but it does sit between the "extreme libertarian and authoritarian approaches" of either entirely permitting or prohibiting certain language online.

Importantly, the user becomes the arbiter. "Many people don't like the idea of an unelected corporation or micromanaging government deciding what we can and can't say to each other," said Tomalin.

"Our system will flag when you should be careful, but it's always your call. It doesn't stop people posting or viewing what they like, but it gives much needed control to those being inundated with hate."

In the paper, the researchers refer to detection algorithms achieving 60% accuracy – not much better than chance. Tomalin's machine learning lab has now got this up to 80%, and he anticipates continued improvement of the mathematical modeling.

Meanwhile, Ullman gathers more 'training data': verified hate speech from which the algorithms can learn. This helps refine the 'confidence scores' that determine a quarantine and subsequent Hate O'Meter read-out, which could be set like a sensitivity dial depending on user preference.

A basic example might involve a word like 'bitch': a misogynistic slur, but also a legitimate term in contexts such as dog breeding. It's the algorithmic analysis of where such a word sits syntactically - the types of surrounding words and semantic relations between them - that informs the hate speech score.

"Identifying individual keywords isn't enough, we are looking at entire sentence structures and far beyond. Sociolinguistic information in user profiles and posting histories can all help improve the classification process," said Ullman.

Added Tomalin: "Through automated quarantines that provide guidance on the strength of hateful content, we can empower those at the receiving end of the hate speech poisoning our online discourses."

However, the researchers, who work in Cambridge's Centre for Research into Arts, Humanities and Social Sciences (CRASSH), say that – as with computer viruses – there will always be an arms race between hate speech and systems for limiting it.

̽��ֱ��project has also begun to look at "counter-speech": the ways people respond to hate speech. ̽��ֱ��researchers intend to feed into debates around how virtual assistants such as 'Siri' should respond to threats and intimidation.

̽��ֱ��work has been funded by the International Foundation for the Humanities and Social Change.

Artificial intelligence is being developed that will allow advisory 'quarantining' of hate speech in a manner akin to malware filters – offering users a way to control exposure to 'hateful content' without resorting to censorship.

We can empower those at the receiving end of the hate speech poisoning our online discourses

Marcus Tomalin

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Opinion: Translation: a bridge between languages that can foster cultural equality

Anonymous — Thu, 09 Jun 2016 15:23:31 +0000

Back in the 1990s, the football manager Dennis Wise was unfazed that some of his new players were foreigners. They would soon be able to communicate, he reassured everyone, since he intended to “learn them a bit of English”.

Earlier this year, David Cameron had the same bright idea. Writing in ̽��ֱ��Times in January, the prime minister lamented that 22% of British Muslim women speak “little or no English”. He argued that it was prohibiting their social integration and holding them back economically. These problems would be solved, he suggested, if these women acquired fluency in English.

̽��ֱ��very fact that this fatuous idea can be solemnly propounded by prominent politicians reveals the extent to which linguistic diversity has become a conundrum in our vast, sprawling, multi-ethnic, multi-lingual, multi-cultural, post-industrial societies.

̽��ֱ��ongoing migration crisis is unparalleled in living memory, and it painfully illustrates how large-scale population displacements can rapidly create social situations in which linguistic differences become flashpoints. ̽��ֱ��inability of migrants to speak the first language of a country to which they have travelled can arouse suspicion and alienation. These differences create divisions that can only be bridged by translating from one language to another, and from one culture to another.

Oddly, we hear little in the media about how translation operates in societies where there are class-based divisions or displaced communities. Some recent research has explored the role of translation in war zones, but this has mainly emphasised the rhetoric of the political elite, rather than the day-to-day linguistic difficulties encountered by civilians caught up in the conflict.

This is disturbing since the power imbalances in any society are manifest in its languages. For instance, Lin Kenan has written at length about how translation could potentially help to trigger social change in China.

Social justice

In this age of relentless globalisation, certain groups of people are routinely disenfranchised due to gender, ethnicity, nationality and social class. In this context, it’s helpful to consider the role translation plays in all of this, and whether it can ever help to empower the disenfranchised – or only serve to increase their vulnerability.

̽��ֱ��controversial translation theorist Lawrence Venuti has argued insistently that fluent translations frequently perpetuate socio-political inequalities. In his view, translation is not an innocuous activity that facilitates communication – it can entrench inequality by bolstering the supremacy of dominant cultures.

Recent research has started to explore these complex issues. ̽��ֱ��translation scholar Israel Hephzibah focuses on English translations of Tamil literature produced by members of the so-called “untouchable” Dalit communities in India. These translations inevitably destabilise the traditional caste system by conferring literary credibility on the writings of a severely marginalised group. Such cases suggest that translation can become aligned with social justice.

Becoming extinct

But the fraught issue of endangered languages and cultures complicates the picture. UNESCO has estimated that 50-90% of the world’s languages will have become extinct by the year 2100.

It has been recognised for some time now that translations of indigenous texts (whether oral or written) can hasten language erosion in communities where there are few surviving native speakers. In contrast, translations into the endangered tongues can help to strengthen those languages.

On the whole, we seem to care less about vanishing languages than we do about endangered species – especially cuddly ones. When the last giant panda finally goes to the great bamboo grove in the sky, there will undoubtedly be prolonged global lamentation. But the Native American Klallam language expired on February 4 2014, when Hazel Sampson (its last speaker) died. Few news organisations felt its passing merited more than a cursory mention.

And even some translation theorists are sceptical. Emily Apter declared bluntly that she has “real reservations” about mingling translation studies and linguistic ecology – the study of how languages interact with their environment. Apter is concerned that the exoticising of expressions by native-speakers and other distinctive characteristics of a language risks imposing a fixed grammar where a natural variation should instead be allowed to prevail.

There are many different kinds of periphery in the modern world, and life close to them can be difficult, even precarious. But languages are spoken there too. They may not be the same languages as those uttered closer to the “centre” of things, but that does not invalidate them.

If we can understand more fully how translation both strengthens and weakens these often disregarded tongues and cultures, then we might be forced to reconsider some of our rather simplistic presuppositions about language and society. And, fortunately, if all else fails, we can always make the world a better place by “learning” everyone a bit of English.

Marcus Tomalin, Research Associate in the Machine Intelligence Laboratory, Department of Engineering, ̽��ֱ�� of Cambridge

This article was originally published on ̽��ֱ��Conversation. Read the original article.

̽��ֱ��opinions expressed in this article are those of the individual author(s) and do not represent the views of the ̽��ֱ�� of Cambridge.

Marcus Tomalin (Department of Engineering) discusses the role of translation in social inequality and social justice.

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Ancient Tamil Script

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