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On a positive note, he says AI has been identified as a key enabler on 79 per cent (134 targets) of the United Nations Sustainable Development Goals (SDGs). However, 35 per cent (59 targets) may experience a negative impact from AI.

Unfortunately, he says unless we start to address the inequities associated with the development of AI right now, were in grave danger of not achieving the UNs SDG goals and, more pertinently, if AI is not properly governed and proper ethics are applied from the beginning, it will have not only a negative physical impact, it will also have a significant social impact globally.

There are significant risks to human dignity and human autonomy, he warns.

If AI is not properly governed and its not underpinned by ethics, it can create socio-economic inequality and impact on human dignity.

A part of the problem at present is most AI is being developed for a commercial outcome, with estimates suggesting its commercial worth to be $15 trillion a year by 2030.

Unfortunately, the path were on poses some significant challenges.

Samarawickrama says AI ethics is underpinned by human ethics and the underlying AI decision-making is driven by data and a hypothesis created by humans.

The danger is much AI is built off the back of the wrong hypothesis because there is an unintentional bias built into the initial algorithm. Every conclusion the AI is making is reached from the hypothesis, which means every decision and the quality of that decision its making is based off a humans ethics and biases.

For Samarawickrama, this huge flaw in AI can only be rectified if diversity, inclusion and socio-economic inequality are taken into account from the very beginning of the AI process.

We can only get to that point if we ensure we have good AI governance and ethics.

The alternative is were basically set up to fail if we do not have that diversity of data.

Much of his work in Australia is with the Australian Red Cross and its parent the International Federation of Red Cross and Red Crescent Societies (IFRC), where he has built a framework linking AI to the seven Red Cross principles in a bid to link AI to the IFRCs global goal of mitigating human suffering.

And while this is enhancing the data literacy across the Red Cross, it also has a potential usage in many organisations, because its about increasing diversity and social justice around AI.

Its a complex problem to solve because there are lot of perspectives as to what mitigating human suffering involves. It goes beyond socio-economic inequality and bias.

For example, the International Committee of the Red Cross is concerned about autonomous weapons and their impact on human suffering.

Samarawickrama says if we are going to achieve the UNSDGs as well as reap the benefits of a $15 trillion a year global economy by 2030, we have to work hard to ensure we get AI right now by focussing on AI governance and ethics.

If we dont, we create a risk of failing to achieve those goals and we need to reduce those by ensuring AI can bring the benefits and value it promises to all of us.

Its why the Red Cross is a good place to start because its all about reducing human suffering, wherever its found and, we need to link that to AI, Samarawickrama says.

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Award-winner warns of the failures of artificial intelligence - The Australian Financial Review

The earliest form of writing originated nearly 5000 years ago in Mesopotamia (present-day Iraq), representing the Sumerian language. However, these early manuscripts, inscriptions, manuals have suffered the wrath of time. Historians have long worried about the missing texts that could give an insight into the life and culture of ancient civilisation, Artificial Intelligence has now come to their aid.

Named after the Greek island in Homers Odyssey, Ithaca, the first deep neural network will help in not only restoring the missing text of damaged inscriptions, but also identifying their original location, and establishing the date they were written. Designed to assist and expand the historians workflow, this AI has achieved 62 per cent accuracy when restoring damaged texts and improved the accuracy of historians from 25 per cent to 72 per cent.

In a study published in the journal Nature, researchers said that models such as Ithaca can unlock the cooperative potential between artificial intelligence and historians, transformationally impacting the way that we study and write about one of the most important periods in human history.

Inspired by biological neural networks, deep neural networks can discover and harness intricate statistical patterns in vast quantities of data. Ithaca is one such development that merges the fields of technology, supercomputing, and ancient history to reveal unknown secrets hidden in plain sight.

Ithaca was trained to simultaneously perform the tasks of textual restoration, geographical attribution, and chronological attribution. Researchers trained the system on inscriptions written in the ancient Greek language and across the ancient Mediterranean world between the seventh century BC and the fifth century AD.

Credit: Ca' Foscari University of Venice

The architecture of Ithaca was carefully tailored to each of the three epigraphic tasks, meaningfully handling long-term context information and producing interpretable outputs to enhance the potential for human-machine cooperation. We believe machine learning could support historians to expand and deepen our understanding of ancient history, just as microscopes and telescopes have extended the realm of science Yannis Assael, Staff Research Scientist at DeepMind said in a statement.

Researchers said that as centuries went by, many ancient inscriptions were damaged and became partially or completely illegible. In some cases, they were removed from their original location, and they can be difficult to date. For instance, 2500 years ago, Greeks started writing on stone, ceramics, and metal, in order to register all sorts of transactions, laws, calendars, and oracles. Today, these archaeological findings reveal a lot of information on the Mediterranean area. Unfortunately, this tale is incomplete.

DeepMind has partnered with Google Cloud and Google Arts & Culture to launch a free interactive version of Ithaca. (File Pic)

Historians have already used Ithaca to shed light on current disputes in Greek history, including the dating of a series of important Athenian decrees thought to have been written before 446/445 BCE. Ithacas average predicted date for the decrees is 421 BCE, aligning with the new evidence and demonstrating how machine learning might contribute to historical debates.

Although it might seem like a small difference, this date shift has significant implications for our understanding of the political history of Classical Athens. We hope that models like Ithaca can unlock the cooperative potential between AI and the humanities, transformationally impacting the way we study and write about some of the most significant periods in human history, Thea Sommerschield, Marie Curie Fellow at Ca' Foscari University of Venice and fellow at Harvard Universitys CHS said.

Historians are now working on other versions of the AI, which has been trained in different ancient languages to study other ancient writing systems, from Akkadian to Demotic and Hebrew to Mayan.

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Meet Ithaca, Artificial Intelligence that will reveal hidden secrets of ancient civilisations - India Today

The JCO is an international, peer-reviewed medical journal published by the American Society of Clinical Oncology (ASCO), with an impact factor (IF) of 44.54. This is the first time that research on AI biomarkers has been published in an international SCI-grade journal of JCO's prestige.

"Immune phenotyping of tumor microenvironment is a logical biomarker for immunotherapy, but objective measurement of such would be extremely challenging," said Professor Tony Mok from the Chinese University of Hong Kong, co-senior author of the journal. "This is the first study that adopted AI technology to define the tumor immune phenotype, and to demonstrate its ability in predicting treatment outcomes of anti-PD-L1 therapy in two large cohorts of patients with advanced non-small cell lung cancer."

Immune checkpoint inhibitors (ICI) are a standard therapy method for advanced NSCLC with programmed death ligand-1 (PD-L1) expression. However, outcomes vary depending on the patient's tumor microenvironment.

Assessing the PD-L1 tumor proportion score (TPS) can bring predictive benefit for patients with high expression (over 50%), who show superior response to ICI therapy over standard chemotherapy. However, ICIs lose their potency in patients with PD-L1 TPS between 1% and 49%, showing outcomes similar to chemotherapy. Therefore, the development of an accuracy-enhanced biomarker to predict ICI response in NSCLC patients with low PD-L1 expression is highly warranted.

While tumor infiltrating lymphocytes (TIL) are promising biomarkers for predicting ICI treatment outcomes apart from PD-L1, clinical application remains challenging as TIL quantification involves a manual evaluation process bound to practical limitations of interobserver bias and intensive labor. Employing AI's superhuman computational capabilities should open new possibilities for the objective quantification of TIL.

To validate immune phenotyping as a complementary biomarker in NSCLC, researchers divided 518 NSCLC patients into three groups based on their tumor microenvironment: inflamed, immune-excluded, and immune-desert. As a result, clinical characteristics based on each immune phenotype group showed statistically significant differences in progression-free survival (PFS) and overall survival (OS).

Furthermore, analysis of NSCLC patients with PD-L1 TPS between 1% and 49% based on their immune phenotype found that the inflamed group showed significantly higher results in objective response rate (ORR) and progression-free survival (PFS), compared to the non-inflamed groups. This shows Lunit SCOPE IO's ability to supplement PD-L1 TPS as a biomarker by accurately predicting immunotherapy response for patients with low PD-L1 TPS.

"Lunit has demonstrated through several abstracts the credibility of Lunit SCOPE IO as a companion diagnostic tool to predict immunotherapy treatment outcomes," said Chan-Young Ock, Chief Medical Officer at Lunit. "This study is a proof-of-concept that compiles all of our past research that elucidates Lunit AI's ability to optimize cancer treatment selection."

Last year, Lunit announced a strategic investment of USD 26 million from Guardant Health, Inc., a leading precision oncology company. Following this major collaboration intended to reshape and innovate the precision oncology landscape, Lunit continues to refine its global position by validating the effectiveness of its AI technology through various studies.

SOURCE Lunit

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Breakthrough Study Validates Artificial Intelligence as a Novel Biomarker in Predicting Immunotherapy Response - Published in Journal of Clinical...

Justin Gomez, a Bay Area native and creator of the Black Lives Matter mural that gained national attention in Martinez, spoke to Diablo Valley College students on Mar. 7 about the events that led to the mural, how it went viral across the internet and how the experience affected his personal life.

In 2020, the Black Lives Matter movement surged in popularity following the murder of George Floyd in Minneapolis, along with other police killings of Black people. Protests erupted across the nation, but Gomez wanted to do something different to make his voice heard.

I had found myself needing to do something, he said. Theres just a feeling of hopelessness and anxiety. And as someone who is a person of color, [I was] thinking about what this moment means for me.

Those feelings prompted him to send a text message call-to-action to 12 people, suggesting they speak out against police brutality and shut down the Martinez Farmers Market with a peaceful protest. More than 300 people showed up for the protest. But that was just the beginning.

White supremacy recruitment flyers were soon posted around Martinez in the weeks following the protest. Seeing the flyers made Gomez upset, but it also motivated him to do something more than just protest, he said. So he reached out to the City of Martinez, which co-signed an agreement to establish a temporary Black Lives Matter mural. On the 4th of July, communities came together and painted a block-long mural that read Black Lives Matter on the streets of Martinez.

But not even one hour after the murals completion, a Trump-supporting couple began to paint over the BLM mural with black paint. The couple hurled verbal abuse at the people who were recording their actions with cell phones, telling them to stop. The mural would be restored by the end of the day, but tensions didnt stop there. The video of the couple went viral, as celebrities and mainstream news outlets reposted the clip. As a result, the District Attorneys office charged the couple with a hate crime.

Within 48 hours I was on the phone with the New York Times and the Washington Post, which felt very surreal, Gomez said. For several days I was on standby with producers from CNN to do a story with Don Lemon.

As the creator of the mural, Gomez also came under direct attack from angered residents. He received many threats some 33 in all including from people photographing his residence. After I started getting all these screenshots sent to me, Im looking at my two small children and my partner and we dont feel safe at our home our home address was published online, he said. Some of Gomezs neighbors experienced harassment as well.

Gomez went online and told people what was happening to him and his family. Close friends and the community then came together to spend time with his family, watching out for them to make sure they remained safe. Finally, to lighten the weight of events and to show that the community would not be intimidated, Gomez helped organize another peaceful protest in the city.

In the aftermath, Gomez said, he felt the City of Martinez had failed in its duty to protect his family despite the numerous threats he was receiving. In terms [of] the city council, there was a complete, total failure of the elected leadership, said Gomez.

The pair of vandals that targeted the BLM mural were ultimately charged and chose to go to trial, but the case has been delayed due to the pandemic. The couple faces other charges as well.

The mural, which was always intended to be temporary, has since been removed. Now, Gomez said, Martinez city officials are trying to come up with a similar project that can be permanent to spread the same message of racial justice.

Theres definitely a desire to recreate something like that somewhere in city space where we can affirm the identities of community members of color here in Martinez.

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How a Black Lives Matter Mural in Martinez Went Viral and Changed Justin Gomez's Life - The Inquirer

The London Metropolitan Police have come under fire under they strip-searched a 15-year-old Black student at her school.

The incident took place at her school in Hackney, East London. Child Q was accused by a teacher of having marijuana in her possession. The teacher reported her and police then strip-searched her without an appropriate adult being present or her mother being contacted.

She was menstruating at the time. No contraband was found in her possession.

Someone walked into the school, where I was supposed to feel safe, took me away from the people who were supposed to protect me and stripped me naked, while on my period, Child Q, said in a statement via her attorney. I cant go a single day without wanting to scream, shout, cry or just give up. I dont know if Im going to feel normal again. But I do know this cant happen to anyone else, ever again.

So theyre doing a March for #ChildQ but theyre marching for black boys and black girls. This is what irritates me. Im not denying what black boys go through in schools, but Child Q is a black girl. And what happened to her is gendered issue rooted in misogynoir.. [cont.] pretty black cute (@afrorckprincess) March 17, 2022

Her attorney also released her own statement: It is unlikely that Child Q would have been treated in this humiliating and degrading way had she not been Black. Child Q and her family are hopeful that the recommendations of the review panel will be carefully considered and implemented so that another child is not exposed to a similar traumatic experience.

Before the strip-search, officers searched the childs bag, blazer, scarf and shoes.

The Independent Office is investigating the case for Police Conduct (IOPC). All three officers are under investigation for potential disciplinary offenses over how Child Q was treated.

My heart breaks for Child Q and her family. Shame on her school and the @metpoliceuk who failed her, abused her & traumatised her. Wishing healing for her and FULL accountability of every adult responsible for this trauma inflicted upon her.

A spokesperson for Black Lives Matter UK expressed its disgust over the incident: Once again, we are reminded of the fact that the police are the perpetrators and there are no lengths they wouldnt go to inflict harm on vulnerable people.

The horrific strip search of a Black girl at school is a clear example of why police should not be in places of education. While politicians have recently called for more police officers to be stationed in schools across the capital, children are being traumatized in spaces that should be safe.

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'Black Lives Matter' Condemns Police After 15-Year-Old Black Girl Is Strip-searched at School: 'Children Are Being Traumatized in Spaces That Should...