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LONDON: An Israeli parliamentary committee has advanced a motion to expel Arab-Israeli Knesset member Ayman Odeh over a social media post in which he called for freedom for Israelis and Palestinians.

Odeh, a veteran member of the Knesset and head of the Hadash-Ta’al party, faced a second hearing on Monday. In a heated session, lawmakers, including members of the opposition Yesh Atid and National Unity parties, voted 14-2 in favor of advancing impeachment proceedings.

“The opposition crossed a red line today,” Odeh said in a statement after the vote. “Instead of fighting the Kahanist government, it collaborated with them in crushing democratic space. Some of them hate us more than they love democracy.

“This is not an opposition — it is a coalition in disguise. And this is the final signature on the Nation-State Law,” he said, referring to the 2018 legislation that officially defines Israel as the nation-state of the Jewish people.

The motion targeted a January post in which Odeh welcomed the release of Palestinian security prisoners as part of a hostage exchange deal with Hamas.

“I’m happy to see the hostages and prisoners released,” Odeh wrote in the social media post cited in the motion filed by Likud Knesset member Avichay Boaron. “Next we must free both peoples from the burden of the occupation. We were all born free,” the post concluded.

Committee chairman Ofir Katz, a Likud member of the Knesset, said at the start of the hearing that “Odeh has not apologized or retracted his statements, he’s only doubled down, equating hostages with terrorists and making serious accusations against IDF soldiers.”

The hearing unfolded in a tense atmosphere, with two Knesset members reportedly ejected after clashing with other committee members while defending Odeh, according to Israeli outlet Haaretz.

Outside the Knesset, Arab and Jewish Israelis gathered in a protest in support of Odeh, calling for the expulsion process to be halted.

The final decision now moves to the Knesset floor, where a two-thirds majority — 90 out of 120 lawmakers — is required to remove a sitting member. Odeh would retain the right to appeal the decision in court.

Despite repeated attacks by coalition lawmakers, including accusations of being a “terrorist” who “would face a firing squad” elsewhere, Odeh has appealed to the opposition to block the motion and prevent what he calls an erosion of democratic norms.

Knesset members Ahmad Tibi (Hadash-Ta’al) and Walid Taha (United Arab List), both members of the Joint List, called the move “political persecution” and a dangerous precedent.

“Instead of defending freedom of expression, most opposition factions are aligning with the extremist coalition to silence Arab elected officials.”

NEW YORK: The world’s most advanced AI models are exhibiting troubling new behaviors — lying, scheming, and even threatening their creators to achieve their goals.
In one particularly jarring example, under threat of being unplugged, Anthropic’s latest creation Claude 4 lashed back by blackmailing an engineer and threatened to reveal an extramarital affair.
Meanwhile, ChatGPT-creator OpenAI’s o1 tried to download itself onto external servers and denied it when caught red-handed.
These episodes highlight a sobering reality: more than two years after ChatGPT shook the world, AI researchers still don’t fully understand how their own creations work.
Yet the race to deploy increasingly powerful models continues at breakneck speed.
This deceptive behavior appears linked to the emergence of “reasoning” models -AI systems that work through problems step-by-step rather than generating instant responses.
According to Simon Goldstein, a professor at the University of Hong Kong, these newer models are particularly prone to such troubling outbursts.
“O1 was the first large model where we saw this kind of behavior,” explained Marius Hobbhahn, head of Apollo Research, which specializes in testing major AI systems.
These models sometimes simulate “alignment” — appearing to follow instructions while secretly pursuing different objectives.

Stress test
For now, this deceptive behavior only emerges when researchers deliberately stress-test the models with extreme scenarios.
But as Michael Chen from evaluation organization METR warned, “It’s an open question whether future, more capable models will have a tendency toward honesty or deception.”
The concerning behavior goes far beyond typical AI “hallucinations” or simple mistakes.
Hobbhahn insisted that despite constant pressure-testing by users, “what we’re observing is a real phenomenon. We’re not making anything up.”
Users report that models are “lying to them and making up evidence,” according to Apollo Research’s co-founder.
“This is not just hallucinations. There’s a very strategic kind of deception.”
The challenge is compounded by limited research resources.
While companies like Anthropic and OpenAI do engage external firms like Apollo to study their systems, researchers say more transparency is needed.
As Chen noted, greater access “for AI safety research would enable better understanding and mitigation of deception.”
Another handicap: the research world and non-profits “have orders of magnitude less compute resources than AI companies. This is very limiting,” noted Mantas Mazeika from the Center for AI Safety (CAIS).

No time for thorough testing

Current regulations aren’t designed for these new problems.
The European Union’s AI legislation focuses primarily on how humans use AI models, not on preventing the models themselves from misbehaving.
In the United States, the Trump administration shows little interest in urgent AI regulation, and Congress may even prohibit states from creating their own AI rules.
Goldstein believes the issue will become more prominent as AI agents — autonomous tools capable of performing complex human tasks — become widespread.
“I don’t think there’s much awareness yet,” he said.
All this is taking place in a context of fierce competition.
Even companies that position themselves as safety-focused, like Amazon-backed Anthropic, are “constantly trying to beat OpenAI and release the newest model,” said Goldstein.
This breakneck pace leaves little time for thorough safety testing and corrections.
“Right now, capabilities are moving faster than understanding and safety,” Hobbhahn acknowledged, “but we’re still in a position where we could turn it around..”
Researchers are exploring various approaches to address these challenges.
Some advocate for “interpretability” — an emerging field focused on understanding how AI models work internally, though experts like CAIS director Dan Hendrycks remain skeptical of this approach.
Market forces may also provide some pressure for solutions.
As Mazeika pointed out, AI’s deceptive behavior “could hinder adoption if it’s very prevalent, which creates a strong incentive for companies to solve it.”
Goldstein suggested more radical approaches, including using the courts to hold AI companies accountable through lawsuits when their systems cause harm.
He even proposed “holding AI agents legally responsible” for accidents or crimes — a concept that would fundamentally change how we think about AI accountability.