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After the November election last year, the national coordinating group of Republican state attorneys general boasted about the success of its aggressive advertising and media campaign against Democrats. The group had used incidents of violence that occurred alongside massive peaceful protests of police killings of unarmed Black men to portray Democrats as "lawless liberals" who "want to burn America."

"Our five-month Lawless Liberals campaign earned millions of impressions" and "emphasized that the Republican AGs are America's strongest defenders of economic freedom, defending the nation from threats of socialism, chaos, and lawlessness," the Republican Attorneys General Association (RAGA) wrote in its press release.

RAGA'scampaign produced at least 17 videos and a website that grossly exaggerated the degree of violence and distorted the positions of Democratic candidates to inspire fear among voters whom they hoped would give Donald Trump a second term as president and vote for other Republicans down the ballot.

As RAGA cynically manipulated the nation's racial strife for political gain, it ignored a very real domestic threat that was snowballing across America. Far-right, violent extremism had been on the rise during the whole Trump administration, and increasing tensions associated with the upcoming elections put the threat into overdrive. Despite attempts by the Trump administration to cover up that threat and inflate the dangers posed by antifascists, anarchistsand BLM protesters, the U.S. Department of Homeland Security concluded that "white supremacist extremists" posed the "most persistent and lethal threat in the Homeland" in its October 2020 threat assessment.

In August, a right-wing police fan and Trump supporter, Kyle Rittenhouse, drove across state lines into Kenosha, Wisconsin, allegedly to protect businesses during a Black Lives Matter protest there. He killed two protesters and injured a third.

But none of that fazed RAGA, which continued to pin violence solely on Black Lives Matter protesters and antifa, the loose network of activistswho work to oppose fascism.

After Trump lost the election, at least 17 Republican attorneys general joined the lame-duck president in disputing the election results. RAGA's nonprofit affiliate, the Rule of Law Defense Fund (RLDF), helped plan the Jan. 6 rally and march that culminated in the pro-Trump insurrection at the Capitol that left five dead, including one Capitol Police officer.

Despite its extensive role in the day's events, RAGA immediately issued a statement praising "the right of Americans to peacefully protest" while condemning "the violence, destruction, and rampant lawlessness occurring at the U.S. Capitol" the same position leading Democrats took on last summer's unrest that RAGA deliberately misrepresented for its own political purposes.

The group's ironic statement from November "RAGA has repeatedly warned that the violence being perpetrated by Democrats would continue even after the Presidential Election" remains online.

Racist fear-mongering is nothing new for the GOP, but over the last six years, Trump became the clear ringleader. Since beginning his first campaign in 2015 with a speech claiming that Mexicans were rapists and drug smugglers, the ex-president's political record was defined by numerous racist statements and actions.

Early in the administration, Trump issued the ban on immigration from majority-Muslim countries (known as the "Muslim ban") and deliberately separated immigrant families. Hundreds or possibly thousands of children are still isolated from their parents, and the Biden administration's effort to reunify the families will be a challenge.

Throughout a term marked by Hatch Act violations, profiteering off the presidencyand potentially criminal attempts to work with a foreign power to swing the 2020 election, Trump tried to label people of color, and those who support their basic human rights, as criminals. He created an office within the Department of Homeland Security (DHS) to highlight crimes committed by immigrants. He falsely characterized the districts represented by Black Democrats, such as the late John Lewis of Georgia or Rep. Ihan Omar of Minnesota, as "crime infested." And he repeatedly circulated videos of random incidents of Black men attacking white people, echoing the "black-on-white crime" myth beloved by white nationalists, including mass murdererDylann Roof.

For years, neo-Nazis and other white nationalists celebrated Trump's racist rhetoric.

"Man, President Trump's Twitter account has been pure fire lately," tweeted prominent neo-Nazi Andrew Anglin. "This is the kind of WHITE NATIONALISM we elected him for."

Meanwhile, the former president lauded or refused to condemn far-right extremists. He famously stated that "very fine people" were among the white nationalists, neo-Nazis, alt-right adherentsand other malicious bigots who came together at the Unite the Right events in Charlottesville, Virginia, in 2017, leading to the murder of a civil rights protester. Trump refused to disavow the right-wing street gang and hate group the Proud Boys or members of the QAnon cult, a far-right, pro-Trump movement predicated on anti-Semitic tropes and wild conspiracy theories. Proud Boys and QAnon fans would feature prominently in the deadly Jan. 6 insurrection.

Trump's anti-Black attacks spiked in 2020 over the backdrop of Black Lives Matter protests, which swept the nation after a white police officer killed an unarmed Black man, George Floyd, by kneeling on his neck for nine straight minutes.

As more than 15 million people of all races marched for basic racial justice, Trump called BLM "a symbol of hate" and signed an executive order aimed at jailing people who damaged monuments to the slaveholding Confederacy and other federal property. The June 2020 order instructed the attorney general to prioritize criminal prosecutions for the destruction of monuments on federal property, with prison sentences of up to 10 years.

That executive order was the excuse that Trump's agencies used for sending unmarked federal agents into Portland, Oregon, to round up leftist protesters. Acting DHS SecretaryChad Wolf issued a dramatic press release at the time, calling protesters who engaged in vandalism "violent anarchists" and referring to their actions as an "attack [on] America" and a "siege."

Expensive property damage occurred at some BLM protests from May to June, but the demonstrations were "remarkably nonviolent," according to research by The Washington Post. "The overall levels of violence and property destruction were low, and most of the violence that did take place was, in fact, directed against the BLM protesters," wrote the authors.

Roughly 93 percent of BLM protests from late May through late August were peaceful, according to a Princeton University study. However, law enforcement intervened more often than in other protests, sometimes escalating tensions and increasing the risk of violence, the study found.

As they inflated the threat posed by leftists, Wolf and his agency attempted to hide the biggest threat facing the U.S.: right-wing extremism. Acting DHS Deputy SecretaryKen Cuccinelli ordered an intelligence official to both exaggerate the threat posed by antifa and anarchist groups and to minimize the threat posed by white supremacist groups, according to a whistleblower complaint.

Trump said he would classify antifa as a terrorist organization, and Republican members of Congress, especially Sen. Ted Cruz, R-Texas, played along.

These distortions were the backdrop for Trump's dishonest 2020 campaign strategy, which borrowed heavily from Richard Nixon's racist "Southern strategy" of the late 1960s. He repeatedly claimed that Democrats and violence in cities led by Democrats would "destroy" the suburbs, a not-so-subtle attempt to scare white suburban voters about crime and entice them to vote for him, the supposed "law and order" candidate.

Trump and his agencies pushed this narrative while police departments knew that far-right actors, who planned to attack protesters and law enforcement, were the primary threat. Many of these threats came from individuals affiliated with the boogaloo movement, a group of heavily armed anti-government extremists who want to incite a civil war. "Boogaloo bois" were among the Capitol insurrectionists, who ended up injuring nearly 140 police officers and killing one. Two other officers died by suicide after the insurrection.

After losing the election, in part because of his poor performance in the suburbs, Trump's increasingly unhinged legal team set out to invalidate the votes of millions of Black voters in cities such as Atlanta, Detroit, Milwaukeeand Philadelphia. The dozens of failed lawsuits filed by Trump campaign and Republican National Committee (RNC) attorneys were so laser-focused on invalidating Black Americans' votes that the NAACP Legal Defense and Educational Fund sued Trump, his campaign, and the RNC in December for conspiring to violate the rights of Black voters.

"By targeting communities of color with false claims of voter fraud, and by coordinating actions to pressure state and local officials to discard votes cast in cities with large Black populations, [the defendants] have undermined our most sacred constitutional values," said Sam Spital, LDF's Director of Litigation.

Multiple lawyers from the Trump and RNC teams risk being disbarred, and some have been sued for defamation.

Trump and RAGA's dishonest and ultimately dangerous actions characterize a broader racist electoral strategy by Republicans at the state and federal levels in 2020. GOP political and advocacy groups and individual candidates used coded language and overt racism in their attempt to scare voters and win elections.

The opening night of the Republican National Convention in August was all about fear. The event featured Charlie Kirk, the head of Turning Point USA, who called Trump "the bodyguard of Western civilization," and Patricia McCloskey, who claimed that Democrats "are not satisfied with spreading the chaos and violence into our communities" and want to "abolish the suburbs altogether." McCloskey and her husband, Mark, infamously brandished guns in their yard during a St. Louis BLM march last summer.

With the president and much of the right-wing think tank and advocacy infrastructure behind them, GOP political candidates ran campaigns directly against BLM and antifa, hoping that their dishonest claims and histrionics would scare voters enough to sweep them into elected office.

Successful Tennessee Senate candidate Bill Hagerty resigned from the board of broker R.J. O'Brien & Associates after the firm tweeted support for BLM. In a statement, Hagerty claimed that BLM"seeks to destroy the nuclear family, calls for violence, promotes anti-Semitism, tears down monuments, and seeks to completely defund and dismantle our police departments."

Former Sen. Kelly Loeffler, who lost her Georgiaseat to Black pastor Raphael Warnock, attacked BLM and members of the WNBA team she co-owns, even going on white supremacist Jack Posobiec's show to do so.

Utah Rep. Burgess Owens, who is Black, compared BLM and antifa to the Ku Klux Klan, a notorious white supremacist organization that lynched Black men. Owens, like several other Republican House freshmen, appeared on QAnon-affiliated podcasts last year as he ran for office. Numerous other Republican members of Congress have bashed BLM, including QAnon adherent, Islamophobeand ant-Semite Rep. Marjorie Taylor Greene, R-Ga., who has called it a domestic terrorist organization. The House stripped Greene of her committee posts on Feb. 4 because of her support for bizarre conspiracy theories and endorsement of violence against Democratic lawmakers in recent years.

Other Republicans ran racist ads, including successful House candidate Bob Good, whose ad claimed that his Black opponent would make people less safe over images of nighttime fires, riotsand arrests.

State and local GOP candidates, including in Texas and Kansas, used racist ads with the same theme: Democrats, under the influence of Black activists and antifascists, will set communities on fire and unleash alarming rates of crime.

Much of the conservative fear-mongering highlighted the phrase "defund the police," a slogan used by activists and some progressive Democrats. Republican campaigns frequently distorted the nature of the position (many who used the phrase supported diverting some money from law enforcement budgets into public programs and did not advocate abolishing law enforcement altogether) and attributed it to candidates who did not want to "defund the police."

It's difficult to evaluate the overall effectiveness of Republicans' racist strategy. The GOP did unexpectedly well in House races, gaining over a dozen seats after many observers expected Democrats to widen their majority, and made slight gains in state elections. But Republicans lost the White House and their Senate majority.

Regardless of how successful the GOP's racist campaigning was, it's already clear that the party has no plans to temper its extremism. The Republican National Committee invited Trump to speak at its spring meeting, and House Minority Leader Kevin McCarthy had "a very good and cordial" meeting with Trump at his Mar-a-Lago resort on Jan. 28 to discuss 2022 electoral strategy.

Despite seven Republican senators joining Democrats in voting to convict the ex-president for inciting the Capitol insurrection the highest number of opposition party votes for impeachment in U.S. history and Senate Minority Leader Mitch McConnell's condemnation of Trump's actions, state parties have rallied around Trump and attacked Republicans who voted to hold him accountable.

The Wyoming GOP censured Rep. Liz Cheney, the House Republican Conference Chair, and asked her to resign after she voted to impeach Trump. The South Carolina GOP censured Rep. Tom Rice for voting to impeach Trump on Jan. 13. The Oregon GOP condemned the 10 Republicans who voted for impeachment and dishonestly called the insurrection a "false flag operation designed to discredit Pres. Trump." The central committee of the North Carolina GOP censured Sen. Richard Burr for his impeachment vote, and the state party in Louisiana censured Sen. Bill Cassidy.

A number of right-wing think tanks and political networks also worked overtime in 2020 to support attacks by Trump and the GOP on BLM and to portray the discussion of the impact of slavery and racism on our country as an attack on American values.

The executive director of the American Legislative Exchange Council (ALEC), a pay-to-play organization that connects corporate lobbyists with conservative state lawmakers to produce model legislation, supported Trump's executive order on monuments. In July, ALEC CEO Lisa Nelson signed a letter backing the order, which portrayed racial justice protesters as "rioters, arsonists, and left-wing extremists" and "the mob." In a nod to Trump's attacks on the 1619 Project, an educational series with the premise that the U.S. was founded on slavery and racism published by The New York Times Magazine, the letter also says that Americans must "teach our history with honesty and respect" and uphold the nation's "culture and values."

Years ago, ALEC worked with the National Rifle Association to write a model bill that became Florida's "Stand Your Ground" legislation, which led to the acquittal of George Zimmerman, the man who killed an unarmed Black teenager, Trayvon Martin, in 2012. Zimmerman's exoneration sparked the first use of the #BlackLivesMatter hashtag on social media.

The Heritage Foundation (co-founded by right-wing activist Paul Weyrich, who also co-founded ALEC)also attacks BLM directly. One article written by two staffers, originally appearing in the conservative New York Post, attributes a "radical, Marxist agenda" to the movement, something it portrays as a grave threat. The article and accompanying video that Heritage produced goes into hysterics over BLM goals, such as making tax codes more progressive and "supporting each other as extended families and 'villages' that collectively care for one another."

A coalition of leaders of ALEC, Heritage's political arm, the Tea Party Patriotsand a Republican front group called Moms for Safe Neighborhoods ran dramatic ads against Biden and Kamala Harris, echoing GOP candidates' claims that Democrats would endanger suburbanites' lives.

Biden & Harris, You're Not Safe With Them from Moms for Safe Neighborhoods on Vimeo.

The Capital Research Center, a right-wing "investigative think tank" and a member of the State Policy Network, has an ongoing series that attempts to discredit BLM. One "special report" titled "Radical Lives Matter" connected BLM with looting and mocked the idea of police brutality. The Capital Research Center is heavily funded by the Bradley Foundation, one of the top funders of right-wing, state-based groups.

As organizations like ALEC and Heritage attacked people's right to challenge racist police killings and promoted a version of U.S. history that diminishes the role that racism and slavery played, one of their main funders bankrolled white nationalist hate groups. DonorsTrust, often known as "the ATM" of the conservative movement, funneled $1.5 million to the VDARE Foundation and $10,500 to the foundation behind the American Renaissance magazine in 2019, CMD first reported. The organizations are two of the most notorious white nationalist outfits in the U.S.

DonorsTrust is a donor-advised fund sponsor, meaning that it manages the individual charitable accounts of its donor clients, who "advise" DonorsTrust on which nonprofits to fund. When CMD asked DonorsTrust CEO Lawson Bader for comment, he mischaracterized his organization's policies, claiming that his group has no control over where its donors direct their funds. However, according to DonorsTrust's own literature, its board determines which nonprofits are eligible for donations.

After Trump fans waged their Jan. 6 insurrection, some Republican members of Congress lied about antifa's involvement and even attempted to blame the violence and deaths on BLM. Others, like Reps. Steve Scalise of Louisianaand Lauren Boebert of Colorado, alleged that by supporting BLM, Democrats had normalized violence. Property destruction last summer was somehow justification for white nationalists, conspiracy theoristsand white militias' storming of the Capitol and plans to execute politicians. Republican members of Congress, including Matt Gaetz of Floridaand Marjorie Taylor Greene, added to this false equivalence by accusing Democrats of hypocrisy for supporting the largely peaceful protests but decrying the anti-democratic invasion of their own workplace.

Andsince the GOP's race-based scare tactics did not succeed at keeping its leader in the White House, the party is now doubling down on racial gerrymandering and voter suppression legislation to reduce turnout in communities of color.

The Brennan Center for Justice anticipates that the GOP will seek to further disenfranchise voters of color as they redraw congressional and state legislative districts, especially in the South, where increased political and racial diversity "pos[es] a serious new threat to the longstanding status quo of white Republican dominance." Republican state lawmakers will control this year's redistricting process in swing states like Florida, Georgiaand Texas.

Seizing on a sea of lies from Trump and other Republicans about nonexistent voter fraud, state lawmakers have also filed more than100 bills to make it more difficult for their constituents to vote by the end of January. If enacted, those measures will reverse 2020's voter turnout progress and impose new, burdensome requirements on voters that disproportionately impact people of color.

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The 2020 Republican campaign: A systematic and sustained attack on people of color - Salon

Artificial Intelligence (AI) systems that interact with us the way we interact with each other have long typified Hollywoods image, whether you think of HAL in 2001: A Space Odyssey, Samantha in Her, or Ava in Ex Machina. It thus might surprise people that making systems that interact, assist or collaborate with humans has never been high on the technical agenda.

From its beginning, AI has had a rather ambivalent relationship with humans. The biggest AI successes have come either at a distance from humans (think of the Spirit and Opportunity rovers navigating the Martian landscape) or in cold adversarial faceoffs (the Deep Blue defeating world chess champion Gary Kasparov, or AlphaGo besting Lee Sedol). In contrast to the magnetic pull of these replace/defeat humans ventures, the goal of designing AI systems that are human-aware, capable of interacting and collaborating with humans and engendering trust in them, has received much less attention.

More recently, as AI technologies started capturing our imaginations, there has been a conspicuous change with human becoming the desirable adjective for AI systems. There are so many variations human-centered, human-compatible, human-aware AI, etc. that there is almost a need for a dictionary of terms. Some of this interest arose naturally from a desire to understand and regulate the impacts of AI technologies on people. In previous columns, I've looked, for example, at bias in AI systems and the impact of AI-generated synthetic reality, such as deep fakes or "mind twins."

This time, let us focus on the challenges and impacts of AI systems that continually interact with humans as decision support systems, personal assistants, intelligent tutoring systems, robot helpers, social robots, AI conversational companions, etc.

To be aware of humans, and to interact with them fluently, an AI agent needs to exhibit social intelligence. Designing agents with social intelligence received little attention when AI development was focused on autonomy rather than coexistence. Its importance for humans cannot be overstated, however. After all, evolutionary theory shows that we developed our impressive brains not so much to run away from lions on the savanna but to get along with each other.

A cornerstone of social intelligence is the so-called theory of mind the ability to model mental states of humans we interact with. Developmental psychologists have shown (with compelling experiments like the Sally-Anne test) that children, with the possible exception of those on the autism spectrum, develop this ability quite early.

Successful AI agents need to acquire, maintain and use such mental models to modulate their own actions. At a minimum, AI agents need approximations of humans task and goal models, as well as the humans model of the AI agents task and goal models. The former will guide the agent to anticipate and manage the needs, desires and attention of humans in the loop (think of the prescient abilities of the character Radar on the TV series M*A*S*H*), and the latter allow it to act in ways that are interpretable to humans by conforming to their mental models of it and be ready to provide customized explanations when needed.

With the increasing use of AI-based decision support systems in many high-stakes areas, including health and criminal justice, the need for AI systems exhibiting interpretable or explainable behavior to humans has become quite critical. The European Unions General Data Protection Regulation posits a right to contestable explanations for all machine decisions that affect humans (e.g., automated approval or denial of loan applications). While the simplest form of such explanations could well be a trace of the reasoning steps that lead to the decision, things get complex quickly once we recognize that an explanation is not a soliloquy and that the comprehensibility of an explanation depends crucially on the mental states of the receiver. After all, your physician gives one kind of explanation for her diagnosis to you and another, perhaps more technical one, to her colleagues.

Provision of explanations thus requires a shared vocabulary between AI systems and humans, and the ability to customize the explanation to the mental models of humans. This task becomes particularly challenging since many modern data-based decision-making systems develop their own internal representations that may not be directly translatable to human vocabulary. Some emerging methods for facilitating comprehensible explanations include explicitly having the machine learn to translate explanations based on its internal representations to an agreed-upon vocabulary.

AI systems interacting with humans will need to understand and leverage insights from human factors and psychology. Not doing so could lead to egregious miscalculations. Initial versions of Teslas auto-pilot self-driving assistant, for example, seemed to have been designed with the unrealistic expectation that human drivers can come back to full alertness and manually override when the self-driving system runs into unforeseen modes, leading to catastrophic failures. Similarly,the systems will need to provide an appropriate emotional response when interacting with humans (even though there is no evidence, as yet, that emotions improve an AI agents solitary performance). Multiple studies show that people do better at a task when computer interfaces show appropriate affect. Some have even hypothesized that part of the reason for the failure of Clippy, the old Microsoft Office assistant, was because it had a permanent smug smile when it appeared to help flustered users.

AI systems with social intelligence capabilities also produce their own set of ethical quandaries. After all, trust can be weaponized in far more insidious ways than a rampaging robot. The potential for manipulation is further amplified by our own very human tendency to anthropomorphize anything that shows even remotely human-like behavior. Joe Weizenbaum had to shut down Eliza, historys first chatbot, when he found his staff pouring their hearts out to it; and scholars like Sherry Turkle continue to worry about the artificial intimacy such artifacts might engender. Ability to manipulate mental models can also allow AI agents to engage in lying or deception with humans, leading to a form of head fakes that will make todays deep fakes tame by comparison. While a certain level of white lies are seen as the glue for human social fabric, it is not clear whether we want AI agents to engage in them.

As AI systems increasingly become human-aware, even quotidian tools surrounding us will start gaining mental-modeling capabilities. This adaptivity can be both a boon and a bane. While we talked about the harms of our tendency to anthropomorphize AI artifacts that are not human-aware, equally insidious are the harms that can arise when we fail to recognize that what we see as a simple tool is actually mental-modeling us. Indeed, micro-targeting by social media can be understood as a weaponized version of such manipulation; people would be much more guarded with social media platforms if they realized that those platforms are actively profiling them.

Given the potential for misuse, we should aim to design AI systems that must understand human values, mental models and emotions, and yet not exploit them with intent to cause harm. In other words, they must be designed with an overarching goal of beneficence to us.

All this requires a meaningful collaboration between AI and humanities including sociology, anthropology and behavioral psychology. Such interdisciplinary collaborations were the norm rather than the exception at the beginning of the AI field and are coming back into vogue.

Formidable as this endeavor might be, it is worth pursuing. We should be proactively building a future where AI agents work along with us, rather than passively fretting about a dystopian one where they are indifferent or adversarial. By designing AI agents to be human-aware from the ground up, we can increase the chances of a future where such agents both collaborate and get along with us.

Subbarao Kambhampati, PhD, is a professor of computer science at Arizona State University and the Chief AI Officer for AI Foundation, which develops realistic AI companions with social skills. He was the president of the Association for the Advancement of Artificial Intelligence, a founding board member of Partnership on AI, and is an Innovators Network Foundation Privacy Fellow. He can be followed on Twitter @rao2z.

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Will Artificial Intel get along with us? Only if we design it that way | TheHill - The Hill

A partnership with startup OfferFit aims to unlock new insights into customer journey mapping with an AI-enabled, self-learning platform.

DALLAS Brinks Home Security has embarked on what it terms an artificial intelligence (AI) transformation in partnership with OfferFit to innovate true 1-to-1 marketing personalization, according to an announcement.

Founded last year, OfferFit uses self-learning AI to personalize marketing offers down to the individual level. Self-learning AI allows companies to scale their marketing offers using real-time results driven by machine learning.

Self-learning AI, also called reinforcement learning, first came to national attention through DeepMinds AlphaGo program, which beat human Go champion Lee Sedol in 2016. While the technology has been used in academic research for years, commercial applications are just starting to be implemented.

Brinks Home Security CEO William Niles approached OfferFit earlier this year about using the AI platform to test customer marketing initiatives, according to the announcement. The pilot program involved using OfferFits proprietary AI to personalize offers for each customer in the sample set.

At first, the AI performed no better than the control. However, within two weeks, the AI had reached two times the performance of the control population. By the end of the third week, it had reached four times the result of the control group, the announcement states.

Brinks Home Security is now looking to expand use cases to other marketing and customer experience campaigns with the goal of providing customers with relevant, personalized offers and solutions.

The companies that flourish in the next decade will be the leaders in AI adoption, Niles says. Brinks Home Security is partnering with OfferFit because we are on a mission to have the best business intelligence and marketing personalization in the industry.

Personalization is a key component in creating customers for life. The consumer electronics industry, in particular, has a huge opportunity to leverage this type of machine learning to provide customers with more meaningful company interactions, not only at the point of sale but elsewhere in the customer lifecycle.

Our goal is to create customers for life by providing a premium customer experience, says Jay Autrey, chief customer officer, Brinks Home Security. To achieve that, we must give each customer exactly the products and services they need to be safe and comfortable in their home. OfferFit lets us reach true one-to-one personalization.

The Brinks Home Security test allowed OfferFit to see its AI adapting through a real-world case. Both companies see opportunities to expand the partnership and its impact on the customer lifecycle.

We know that AI is the future of marketing personalization, and pilot programs like the one that Brinks Home Security just completed demonstrate the value that machine learning can have for a business and on its customers, comments OfferFit CEO George Khachatryan.

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Brinks Home Security Will Leverage AI to Drive Customer Experience - Security Sales & Integration

Why the Navy should build unmanned fighters as well as unmanned vessels Back to the future: the X-47B unmanned fighter prototype aboard the carrier USS George H.W. Bush, 2013 (USN)

By CIMSEC 02-28-2021 08:02:00

[ByTrevor Phillips-Levine, Dylan Phillips-Levine, and Walker D. Mills]

In August 2020, USNI News reported that the Navy had initiated work to develop its first new carrier-based fighter in almost 20 years. While the F-35C Lightning II will still be in production for many years, the Navy needs to have another fighter ready to replace the bulk of the F/A-18E/F/G Super Hornets and Growlers by the mid-2030s. This new program will design that aircraft. While this is an important development, it will be to the Navys detriment if the Next Generation Air Dominance (NGAD) program yields a manned fighter.

Designing a next-generationmannedaircraft will be a critical mistake. Every year remotely piloted aircraft (RPAs) replace more and more manned aviation platforms, and artificial intelligence (AI) is becoming ever increasingly capable. By the mid-2030s, when the NGAD platform is expected to begin production, it will be obsolete on arrival if it is a manned platform. In order to make sure the Navy maintains a qualitative and technical edge in aviation, it needs to invest in an unmanned-capable aircraft today. Recent advances and long-term trends in automation and computing make it clear that such an investment is not only prudent but necessary to maintain capability overmatch and avoid falling behind.

Artificial Intelligence

This year, AI designed by a team from Heron Systems defeated an Air Force pilot, call sign Banger, 5-0 in a simulated dogfight run by DARPA. Though the dogfight was simulated and had numerous constraints, it was only the latest in a long string of AI successes in competitions against human masters and experts.

Since 1997, when IBMs DeepBlue beat the reigning world chess champion Gary Kasparov over six games in Philadelphia, machines have been on a winning streak against humans. In 2011,IBMs Watson wonJeopardy!.In 2017, DeepMinds (Google) AlphaGobeat the worlds number one Go playerat the complex Chinese board game. In 2019, DeepMinds AlphaStarbeat one of the worlds top-ranked Starcraft II players, a real-time computerstrategy game, 5-0. Later that year an AI from Carnegie Mellon named Pluribus beat six professionals in a game of Texas Holdem poker.On the lighter side,an AI writing algorithm nearly beat the writing team for the game Cards Against Humanityin a competition to see who could sell more card packs in a Black Friday write-off. After the contest the companys statement read: The writers sold 2% more packs, so their jobs will be replaced by automation later instead of right now. Happy Holidays.

Its a joke, but the company is right. AI is getting better and better every year and human abilities will continue to be bested by AI in increasingly complex and abstract tasks. History shows that human experts have been repeatedly surprised by AIs rapid progress and their predictions on when AI will reach human parity in specific tasksoften come true years or a decade early. We cant make the same mistake with unmanned aviation.

Feb, 11, 1996 Garry Kasparov, left, reigning world chess champion, plays a match against IBMs Deep Blue, in the second of a six-game match in Philadelphia. Moving the chess pieces for IBMs Deep Blue is Feng-hsiung Hsu, architect and principal designer of the Deep Blue chess machine. (H. Rumph, Jr./AP File)

Most of these competitive AIs use machine learning. A subset of machine learning is deep reinforcement learning which uses biologically inspired evolutionary techniques to pit a model against itself over and over. Models that that are more successful at accomplishing the specific goal such as winning at Go or identifying pictures of tigers, continue on. It is like a giant bracket, except that the AI can compete against itself millions or even billions of times in preparation to compete against a human. Heron Systems AI, which defeated the human pilot, had run over four billion simulations before the contest. The creators called it putting a baby in the cockpit. The AI was given almost no instructions on how to fly, so even basic practices like not crashing into the ground were things it had to learn through trial and error.

This type of training has advantages algorithms can come up with moves that humans have never thought of, or use maneuvers humans would not choose to utilize. In the Go matches between Lee SeDol and AlphaGo, the AI made a move on turn 37, in game two, that shocked the audience and SeDol. Fan Hui, a three-time European Go champion and spectator of the match said, Its not a human move. Ive never seen a human play this move. It is possible that the move had never been played before in the history of the game. In the AlphaDogfight competition, the AI favored aggressive head-on gun attacks. This tactic is considered high-risk and prohibited in training. Most pilots wouldnt attempt it in combat. But an AI could. AI algorithms can develop and employ maneuvers that human pilots wouldnt think of or wouldnt attempt. They can be especially unpredictable in combat against humans because they arent human.

An AI also offers significant advantages over humans in piloting an aircraft because it is not limited by biology. An AI can make decisions in fractions of a second and simultaneously receive input from any number of sensors. It never has to move its eyes or turn its head to get a better look. In high-speed combat where margins are measured in seconds or less, this speed matters. An AI also never gets tired it is immune to the human factors of being a pilot. It is impervious to emotion, mental stress, and arguably the most critical inhibitor, the biological stresses of high-G maneuvers. Human pilots have a limit to their continuous high-G maneuver endurance. In the AlphaDogfight, both the AI and Banger, the human pilot, spent several minutes in continuous high-G maneuvers. While high G-maneuvers would be fine for an AI, real combat would likely induce loss of consciousness or G-LOC for human pilots.

Design and Mission Profiles

Aircraft, apart from remotely piloted aircraft (RPAs), are designed with a human pilot in mind. It is inherent to the platform that it will have to carry a human pilot and devote space and systems to all the necessary life support functions. Many of the maximum tolerances the aircraft can withstand are bottlenecked not by the aircraft itself, but to its pilot. An unmanned aircraft do not have to worry about protecting a human pilot or carrying one. It can be designed solely for the mission.

Aviation missions are also limited to the endurance of human pilots, where there is a finite number of hours a human can remain combat effective in a cockpit. Using unmanned aircraft changes that equation so that the limit is the capabilities of the aircraft and systems itself. Like surveillance drones, AI-piloted aircraft could remain on station for much longer than human piloted aircraft and (with air-to-air refueling) possibly for days.

The future operating environment will be less and less forgiving for human pilots. Decisions will be made at computational speed which outpaces a human OODA loop. Missiles will fly at hypersonic speeds and directed energy weapons will strike targets at the speed of light.Lockheed Martin has set a goal for mounting lasers on fighter jets by 2025. Autonomous aircraft piloted by AI will have distinct advantages in the future operating environment because of the quickness of its ability to react and the indefinite sustainment of that reaction speed. The Navy designed the Phalanx system to be autonomous in the 1970s and embedded doctrine statements into the Aegis combat system because it did not believe that humans could react fast enough in the missile age threat environment. The future will be even more unforgiving with a hypersonic threat environment and decisions made at the speed of AI that will often trump those made at human speeds in combat.

Unmanned aircraft are also inherently more risk worthy than manned aircraft. Commanders with unmanned aircraft can take greater risks and plan more aggressive missions that would have featured an unacceptably low probability of return for manned missions. This increased flexibility will be essential in rolling back and dismantling modern air defenses and anti-access, area-denial networks.

Unmanned is Already Here

The U.S. military already flies hundreds of large RPAs like the MQ-9 Predator and thousands of smaller RPAs like the RQ-11 Raven. It uses these aircraft for reconnaissance, surveillance, targeting, and strike. TheMarine Corps has flown unmanned cargo helicopters in Afghanistanand other cargo-carrying RPAs andautonomous aircrafthave proliferated in the private sector. These aircraft have been displacing human pilots in the cockpit for decades with human pilots now operating from the ground. The dramatic proliferation of unmanned aircraft over the last two decades has touched every major military and conflict zone. Even terrorists and non-state actors are leveraging unmanned aircraft for both surveillance and strike.

Apart from NGAD, the Navy is going full speed ahead on unmanned and autonomous vehicles.Last year it awarded a $330 million dollar contract for a medium-sized autonomous vessel. In early 2021, the Navy plans to runalarge Fleet Battle Problem exercise centered on unmanned vessels.The Navy has also begun to supplement its MH-60S squadrons with the unmanned MQ-8B. Chief among its advantages over the manned helicopter is the long on-station time. The Navy continues toinvest in its unmanned MQ-4C maritime surveillance dronesand has nowflight-tested the unmanned MQ-25 Stingray aerial tanker. In fact, the Navy has so aggressively pursued unmanned and autonomous vehicles that Congress has tried toslow down its speed of adoption and restrict some funding.

The Air Force too has been investing in unmanned combat aircraft. The unmanned loyal wingman drone is already being tested and in 2019 the service released itsArtificial Intelligence Strategyarguing that AI is a capability that will underpin our ability to compete, deter and win. The service is also moving forward with testing their Golden Horde, an initiative to create a lethal swarm of autonomous drones.

The Marine Corps has also decided to bet heavily on an unmanned future. In the recently releasedForce Design 2030 Report, the Commandant of the Marine Corps calls for doubling the Corps unmanned squadrons. Marines are alsodesigning unmanned ground vehiclesthat will be central to their new operating concept, Expeditionary Advanced Base Operations (EABO) andnew, large unmanned aircraft. Department of the Navy leaders have said that they would not be surprised if as much as 50 percent of Marine Corps aviation is unmanned relatively soon. The Marine Corps is also investing in a new family of systems to meet its requirement for ship-launched drones. With so much investment in other unmanned and autonomous platforms, why is the Navy not moving forward on an unmanned NGAD?

Criticism

An autonomous, next-generation combat aircraft for the Navy faces several criticisms. Some concerns are valid while others are not. Critics can rightly point out that AI is not ready yet. While this is certainly true, it likely will be ready enough by the mid-2030s when the NGAD is reaching production. 15 years ago, engineers were proud of building a computer that could beat Gary Kasparov at chess. Today, AIs have mastered ever more complex real-time games and aerial dogfighting. One can only expect AI will make a similar if not greater leap in the next 15 years. We need to be future-proofing future combat aircraft. So the question should not be, Is AI ready now? but, Will AI be ready in 15 years when NGAD is entering production?

Critics of lethal autonomy should note that it is already here. Loitering munitions are only the most recent manifestation of weapons without a human in the loop. The U.S. military has employed autonomous weapons ever since Phalanx was deployed on ships in the 1970s, and more recently with anti-ship missiles featuring intelligent seeker heads. The Navy is also simultaneously investing in autonomous surface vessels and unmanned helicopters, proving that there is room for lethal autonomy in naval aviation.

Some have raised concerns that autonomous aircraft can be hacked and RPAs can have their command and control links broken, jammed, or hijacked. But these concerns are no more valid with unmanned aircraft than manned aircraft. Modern 5thgeneration aircraft are full of computers, networked systems, and use fly-by-wire controls. A hacked F-35 will be hardly different than a hacked unmanned aircraft, except there is a human trapped aboard. In the case of RPAs, they have lost link protocols that can return them safely to base if they lose contact with a ground station.

Unfortunately, perhaps the largest obstacle to an unmanned NGAD is imagination. Simply put, it is difficult for Navy leaders, often pilots themselves, to imagine a computer doing a job that they have spent years mastering. They often consider it as much an art as a science. But these arguments sound eerily similar to arguments made by mounted cavalry commanders in the lead up to the Second World War. As late as 1939, Army General John K. Kerr argued that tanks could not replace horses on the battlefield. He wrote: We must not be misled to our own detriment to assume that the untried machine can displace the proved and tried horse. Similarly, the U.S. Navy was slow to adopt and trust search radars in the Second World War. Of their experience in Guadalcanal, historianJames D. Hornfischerwrote, The unfamiliar power of a new technology was seldom a match for a complacent human mind bent on ignoring it. Today we cannot make the same mistakes.

Conclusion

The future of aviation is unmanned aircraft whether remotely piloted, autonomously piloted, or a combination. There is simply no reason that a human needs to be in the cockpit of a modern, let alone next-generation aircraft. AI technology is progressing rapidly and consistently ahead of estimates. If the Navy waits to integrate AI into combat aircraft until it is mature, it will put naval aviation a decade or more behind.

Platforms being designed now need to be engineered to incorporate AI and future advances. Human pilots will not be able to compete with mature AI already pilots are losing to AI in dogfights; arguably the most complex part of their skillset. The Navy needs to design the next generation of combat aircraft for unmanned flight or it risks making naval aviation irrelevant in the future aerial fight.

TrevorPhillips-Levine is a lieutenant commander in the United States Navy. He has flown the F/A-18 Super Hornet in support of operations New Dawn and Enduring Freedom and is currently serving as a department head in VFA-2.

Dylan Phillips-Levine is a lieutenant commander in the United States Navy. He has flown the T-6B Texan II as an instructor and the MH-60R Seahawk. He is currently serving as an instructor in the T-34C-1 Turbo-Mentor as anexchange instructor pilot with the Argentine navy.

Walker D. Mills is a captain in the Marines. An infantry officer, he is currently serving as an exchange instructor at the Colombian naval academy. He is an Associate Editor at CIMSEC and an MA student at the Center for Homeland Defense and Security at the Naval Postgraduate School.

This article appears courtesy of CIMSEC and may be found in its original form here.

The opinions expressed herein are the author's and not necessarily those of The Maritime Executive.

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The Future is Unmanned - The Maritime Executive

WASHINGTONDemocrats are resorting to a well-worn tactic for their plan to expand the child tax credit: Push for a short-term policy, then highlight the consequences of letting it expire as scheduled.

The expansion of the credit would send money to households, increasing the benefit to $3,000 a child from $2,000 while adding a $600 bonus for children under age 6. It is a key piece of the $1.9 trillion pandemic-relief plan that the House passed on Saturday and that the Senate will consider this week.

Advocates say the bill would cut child poverty in half. But that larger credit is scheduled to last only through 2021, and its backers are already warning what will happen if it expires and urging a permanent extension.

Were really confident that Congress is not going to want to double the child poverty rate in this country, Sen. Michael Bennet (D., Colo.) told reporters last week.

Once the larger credit is in place, it wont go away, regardless of the Dec. 31 expiration date, predicted Brian Riedl, a former Senate GOP aide who is now a senior fellow at the Manhattan Institute, a conservative think tank.

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Democrats Seek Temporary Expansion of Child Tax Credit, but Making It Permanent Is Real Goal - The Wall Street Journal