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Meet the LGBTQ activists fighting to be themselves online in Malaysia

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Meet the LGBTQ activists fighting to be themselves online in Malaysia


Many online attacks on LGBTQ Malaysians start with their fellow social media users (although some suspect that political or religious groups may be helping coordinate them). Individual threats can escalate. When a social media post or account is deemed “insulting to Islam” and reported to police, for example, the poster can face state surveillance, arrest, and prosecution. Many of these responses are carried out under the auspices of the controversial Multimedia and Communication Act, a law passed in 1998 that gives authorities broad powers to regulate media and communications in the country.

After the government threatened him with prosecution for organizing an LGBTQ event, Numan Afifi, one of Malaysia’s most high-profile activists, packed a suitcase, quit his job, and fled the country in July 2017. He spent six months moving among six different countries, often sleeping on couches, with no income and no idea if he would return. He says law firms offered him pro bono support for seeking asylum.

But ahead of the 2018 election, which many hoped would usher in a more progressive government, Afifi headed home instead. “I decided to return believing in my Malaysian dream,” he tweeted of the period in 2019. “I still believe in that dream, for myself, and for thousands of struggling gay kids in our schools that were like me.” Doesn’t he feel at risk? “Yes, all the time,” he says. “But you still have to do it because people need our services. I have to do it.”

Pakatan Harapan, a coalition thought to be on the more progressive end of the political spectrum, did win Malaysia’s May 2018 election. And at first, there were signs the group aimed to fulfill its promise to put improvements in human rights, including LGBTQ rights, at the top of its political agenda. A week into the administration, Afifi himself was appointed to be a press officer by the minister for youth and sports. In July, the newly appointed religious affairs minister called for an end to discrimination against LGBTQ people in the workplace, which was seen as a significant break from the status quo. But within months there were a series of high-profile regressions. Afifi resigned as public backlash grew over the appointment of an LGBTQ activist. Police raided a Kuala Lumpur nightclub popular with gay men. Two women were arrested and caned for “attempting lesbian sex” in a car.

Since the 2018 election, human rights campaigners have warned of a worrying erosion in human rights in the country, one that extends beyond the treatment of LGBTQ communities to the treatment of migrants and broader questions of censorship and freedom of expression. In June 2021, during Pride Month, a government task force even went so far as to propose widening an existing Sharia law that already allows action to be taken against those who insult Islam, to specifically target people who “promote LGBT lifestyles” online. “Things have just gotten worse, like really, really bad,” says one activist, who asked to remain anonymous for safety reasons. “I don’t know what’s going to happen.” 

Despite the risks, many activists are unequivocal: if online platforms are the latest battleground for LGBTQ rights, that is exactly where they’ll make their stand. 

At organizations such as the trans-led SEED Foundation in Kuala Lumpur, for example, experts have been brought in to train members about the intricacies of cybersecurity, teaching them how to prevent devices from being tracked, protect social media accounts from being hacked, and stop emails from being traced.

Malaysian authorities routinely cite their powers under Section 233 of the Multimedia and Communication Act to block access to websites, private blogs, and news articles. The law allows any content deemed “obscene, indecent, false, menacing, or offensive” to be removed, a definition that has been used to censor international LGBTQ websites, such as Planet Romeo and Gay Star News. Though equally vulnerable, smaller domestic sites have so far avoided this fate. But many remain vigilant about digital security. One activist says the site she’s involved with faces hacks as often as every six months. “We have to think about back-end security all of the time, with risk assessments for everything we do,” she adds. 



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The Download: how we can limit global warming, and GPT-4’s early adopters

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The UN just handed out an urgent climate to-do list. Here’s what it says.


Time is running short to limit global warming to 1.5°C (2.7 °F) above preindustrial levels, but there are feasible and effective solutions on the table, according to a new UN climate report.

Despite decades of warnings from scientists, global greenhouse-gas emissions are still climbing, hitting a record high in 2022. If humanity wants to limit the worst effects of climate change, annual greenhouse-gas emissions will need to be cut by nearly half between now and 2030, according to the report.

That will be complicated and expensive. But it is nonetheless doable, and the UN listed a number of specific ways we can achieve it. Read the full story.

—Casey Crownhart

How people are using GPT-4

Last week was intense for AI news, with a flood of major product releases from a number of leading companies. But one announcement outshined them all: OpenAI’s new multimodal large language model, GPT-4. William Douglas Heaven, our senior AI editor, got an exclusive preview. Read about his initial impressions.  

Unlike OpenAI’s viral hit ChatGPT, which is freely accessible to the general public, GPT-4 is currently accessible only to developers. It’s still early days for the tech, and it’ll take a while for it to feed through into new products and services. Still, people are already testing its capabilities out in the open. Read about some of the most fun and interesting ways they’re doing that, from hustling up money to writing code to reducing doctors’ workloads.

—Melissa Heikkilä

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Google just launched Bard, its answer to ChatGPT—and it wants you to make it better

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Google just launched Bard, its answer to ChatGPT—and it wants you to make it better


Google has a lot riding on this launch. Microsoft partnered with OpenAI to make an aggressive play for Google’s top spot in search. Meanwhile, Google blundered straight out of the gate when it first tried to respond. In a teaser clip for Bard that the company put out in February, the chatbot was shown making a factual error. Google’s value fell by $100 billion overnight.

Google won’t share many details about how Bard works: large language models, the technology behind this wave of chatbots, have become valuable IP. But it will say that Bard is built on top of a new version of LaMDA, Google’s flagship large language model. Google says it will update Bard as the underlying tech improves. Like ChatGPT and GPT-4, Bard is fine-tuned using reinforcement learning from human feedback, a technique that trains a large language model to give more useful and less toxic responses.

Google has been working on Bard for a few months behind closed doors but says that it’s still an experiment. The company is now making the chatbot available for free to people in the US and the UK who sign up to a waitlist. These early users will help test and improve the technology. “We’ll get user feedback, and we will ramp it up over time based on that feedback,” says Google’s vice president of research, Zoubin Ghahramani. “We are mindful of all the things that can go wrong with large language models.”

But Margaret Mitchell, chief ethics scientist at AI startup Hugging Face and former co-lead of Google’s AI ethics team, is skeptical of this framing. Google has been working on LaMDA for years, she says, and she thinks pitching Bard as an experiment “is a PR trick that larger companies use to reach millions of customers while also removing themselves from accountability if anything goes wrong.” 

Google wants users to think of Bard as a sidekick to Google Search, not a replacement. A button that sits below Bard’s chat widget says “Google It.” The idea is to nudge users to head to Google Search to check Bard’s answers or find out more. “It’s one of the things that help us offset limitations of the technology,” says Krawczyk.

“We really want to encourage people to actually explore other places, sort of confirm things if they’re not sure,” says Ghahramani.

This acknowledgement of Bard’s flaws has shaped the chatbot’s design in other ways, too. Users can interact with Bard only a handful of times in any given session. This is because the longer large language models engage in a single conversation, the more likely they are to go off the rails. Many of the weirder responses from Bing Chat that people have shared online emerged at the end of drawn-out exchanges, for example.   

Google won’t confirm what the conversation limit will be for launch, but it will be set quite low for the initial release and adjusted depending on user feedback.

Bard in action

GOOGLE

Google is also playing it safe in terms of content. Users will not be able to ask for sexually explicit, illegal, or harmful material (as judged by Google) or personal information. In my demo, Bard would not give me tips on how to make a Molotov cocktail. That’s standard for this generation of chatbot. But it would also not provide any medical information, such as how to spot signs of cancer. “Bard is not a doctor. It’s not going to give medical advice,” says Krawczyk.

Perhaps the biggest difference between Bard and ChatGPT is that Bard produces three versions of every response, which Google calls “drafts.” Users can click between them and pick the response they prefer, or mix and match between them. The aim is to remind people that Bard cannot generate perfect answers. “There’s the sense of authoritativeness when you only see one example,” says Krawczyk. “And we know there are limitations around factuality.”

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How AI experts are using GPT-4

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How AI experts are using GPT-4


Hoffman got access to the system last summer and has since been writing up his thoughts on the different ways the AI model could be used in education, the arts, the justice system, journalism, and more. In the book, which includes copy-pasted extracts from his interactions with the system, he outlines his vision for the future of AI, uses GPT-4 as a writing assistant to get new ideas, and analyzes its answers. 

A quick final word … GPT-4 is the cool new shiny toy of the moment for the AI community. There’s no denying it is a powerful assistive technology that can help us come up with ideas, condense text, explain concepts, and automate mundane tasks. That’s a welcome development, especially for white-collar knowledge workers. 

However, it’s notable that OpenAI itself urges caution around use of the model and warns that it poses several safety risks, including infringing on privacy, fooling people into thinking it’s human, and generating harmful content. It also has the potential to be used for other risky behaviors we haven’t encountered yet. So by all means, get excited, but let’s not be blinded by the hype. At the moment, there is nothing stopping people from using these powerful new  models to do harmful things, and nothing to hold them accountable if they do.  

Deeper Learning

Chinese tech giant Baidu just released its answer to ChatGPT

So. Many. Chatbots. The latest player to enter the AI chatbot game is Chinese tech giant Baidu. Late last week, Baidu unveiled a new large language model called Ernie Bot, which can solve math questions, write marketing copy, answer questions about Chinese literature, and generate multimedia responses. 

A Chinese alternative: Ernie Bot (the name stands for “Enhanced Representation from kNowledge IntEgration;” its Chinese name is 文心一言, or Wenxin Yiyan) performs particularly well on tasks specific to Chinese culture, like explaining a historical fact or writing a traditional poem. Read more from my colleague Zeyi Yang. 

Even Deeper Learning

Language models may be able to “self-correct” biases—if you ask them to

Large language models are infamous for spewing toxic biases, thanks to the reams of awful human-produced content they get trained on. But if the models are large enough, they may be able to self-correct for some of these biases. Remarkably, all we might have to do is ask.

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